Abstract:
The SNMP cache of the present solution supports multi-core/multi-node environment by recalculating the SNMP ordering of the entities in the response from multiple cores/nodes at insertion time. The most significant gain is achieved by prefetching or augmenting the cache, wherein while requesting an entity and its stat information, next few entities in SNMP order are requested from the owner processes. SNMP Management systems extensively utilize repeated GETNEXT (such as via a SNMP WALK) and few next responses may be served from the cache directly. Further performance improvements are obtained by introducing another level of cache on top of the existing cache. This auxiliary cache ensures a high hit ratio for repeated SNMP GETNEXT request (SNMP WALK operation) by caching last accessed entity within the main cache. This auxiliary cache also aids in insertion in the larger main cache by maintaining pointers to last accessed entity before the main cache miss. Cache implements other features like new stat inclusion/updating of the already cached entity.

Description:
RELATED APPLICATION 
     The present application claims the benefit of and priority to U.S. Provisional Application No. 61/624,126, entitled “Systems and Methods For Caching SNMP Data In Multi-Core and Cluster Systems” and filed on Apr. 13, 2012, which is incorporated herein by reference in its entirety for all purposes. 
     FIELD 
     The present application generally relates to data communication networks. In particular, the present application relates to systems and methods for caching Simple Network Management Protocol (SNMP) data across multi-core and clustered networking devices. 
    
    
     BACKGROUND 
     A device may responds to SNMP queries from a management system for a number of managed objects including singular and tabular data. In multi-node and clustered systems, data for these managed objects are dynamic and are collected across each of the cores in multi-core devices and across each of the nodes in clusters. When scaling to a large number of managed objects, the performance of such systems may be significantly decreased. 
     BRIEF SUMMARY 
     The present solution is directed towards SNMP caching in multi-core and clustered network devices. While a simple cache implementation can work for SNMP GET requests, a majority of SNMP requests are GETNEXT. The requesting system manager expects the next SNMP object instance value in lexicographic object identifier (OID) order as a response, which usually is the statistic (e.g., stat) of the next entity. The present solution provides a dynamic cache of SNMP managed object instances, such as tabular data type objects, which can reliably insert, invalidate, flush and determine cache hit/miss for GETNEXT requests together with GET requests. This cache implementation stores partial cluster/multi-core entities configuration and stat info with default cache ordering and explicit SNMP lexicographic ordering maintained among these entities. SNMP ordering is used to determine a cache hit for GETNEXT. A cache hit includes capability of determining whether an entity is not present at all in the system. In certain cases, the cache inserts a dummy entity for marking the start and end of the SNMP ordering. Partial cache invalidations and deletions are associated with invalidating the SNMP ordering of relevant entities and the cache still works for GET operations over these entities and GETNEXT for other entities with SNMP ordering intact. 
     The SNMP cache of the present solution supports multi-core/multi-node environment by recalculating the SNMP ordering of the entities in the response from multiple cores/nodes at insertion time. The most significant gain is achieved by prefetching or augmenting the cache, wherein while requesting an entity and its stat information, next few entities in SNMP order are requested from the owner processes. SNMP Management systems extensively utilize repeated GETNEXT (such as via a SNMP WALK) and few next responses may be served from the cache directly. Further performance improvements are obtained by introducing another level of cache on top of the existing cache. This auxiliary cache ensures a high hit ratio for repeated SNMP GETNEXT request (SNMP WALK operation) by caching last accessed entity within the main cache. This auxiliary cache also aids in insertion in the larger main cache by maintaining pointers to last accessed entity before the main cache miss. Cache implements other features like new stat inclusion/updating of the already cached entity. 
     In some aspects, the present solution is directed to a method for providing a Simple Network Management Protocol (SNMP) cache. The method includes establishing, by a device, a Simple Network Management Protocol (SNMP) cache. The SNMP cache storing managed objects in a predetermined lexicographic order. The method further includes transmitting, by a cache manager of the SNMP cache, one or more SNMP GETNEXT requests to one or more managed information bases to get one or more managed objects and storing the one or more managed objects in their predetermined lexicographic order in the SNMP cache. 
     In some embodiments, the method includes receiving, by the device, a SNMP GETNEXT request and determining, by the device responsive to the SNMP GETNEXT request, that a managed object corresponding to a next object in lexicographical order is stored in the SNMP cache and serving the managed object from the SNMP cache as a response to the SNMP GETNEXT request. In some embodiments, the method includes establishing the SNMP cache by the device intermediary to a plurality of clients and a plurality of servers. The device responds to SNMP GETNEXT requests with managed objects stored in the SNMP cache. 
     In some embodiments, the method includes ordering, by the cache manager, the managed objects in the cache by the predetermined lexicographic order based on their corresponding object identifiers. In some embodiments, the method includes transmitting, by the cache manager, the one or more SNMP GETNEXT requests to prefetch a predetermined set of managed objects. In some embodiments, the method includes receiving, by the cache manager, a SNMP GET request for a managed object identified by an object identifier. In some embodiments, the method includes transmitting, by the cache manager responsive to the SNMP GET request, the one or more SNMP GETNEXT requests to the one or more managed information bases for the one or more managed objects next in the lexicographical order. 
     In some embodiments, the method includes establishing, by the device, an auxiliary cache in association with the SNMP cache. The auxiliary cache stores one or more pointers to managed objects stored in the SNMP cache. In some embodiments, the maintaining in the auxiliary cache one or more pointers to the managed objects that were last accessed in the SNMP cache over a predetermined time period. 
     In some aspects, the present solution is directed to a system for providing a Simple Network Management Protocol (SNMP) cache. The system includes a device configured to establish a Simple Network Management Protocol(SNMP) cache. The SNMP cache configured to store managed objects in a predetermined lexicographic order. The system includes a cache manager of the SNMP cache configured to transmit one or more SNMP GETNEXT requests to one or more managed information bases to get one or more managed objects and to store the one or more managed objects in their predetermined lexicographic order in the SNMP cache. 
     In some embodiments, the device is further configured to receive a SNMP GETNEXT request. In some embodiments, the device is further configured, responsive to the SNMP GETNEXT request, to determine that a managed object corresponding to a next object in lexicographical order is stored in the SNMP cache and serve the managed object from the SNMP cache as a response to the SNMP GETNEXT request. In some embodiments, the device is configured to be deployed intermediary to a plurality of clients and a plurality of servers. The device is further to consider to respond to SNMP GETNEXT requests with managed objects stored in the SNMP cache. 
     In some embodiments, the cache manager is configured to order the managed objects in the cache by the predetermined lexicographic order based on their corresponding object identifiers. In some embodiments, the cache manager is configured to transmit the one or more SNMP GETNEXT requests to prefetch a predetermined set of managed objects. In some embodiments, the cache manager is configured to receive a SNMP GET request for a managed object identified by an object identifier. In some embodiments, the cache manager is configured to, responsive to the SNMP GET request, to transmit the one or more SNMP GETNEXT requests to the one or more managed information bases for the one or more managed objects next in the lexicographical order. 
     In some embodiments, the device is configured to establish an auxiliary cache in association with the SNMP cache. The auxiliary cache configured to store one or more pointers to managed objects stored in the SNMP cache. The auxiliary cache is further configured to maintain one or more pointers to the managed objects that were last accessed in the SNMP cache over a predetermined time period. 
     The details of various embodiments of the invention are set forth in the accompanying drawings and the description below. 
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
       The foregoing and other objects, aspects, features, and advantages of the invention will become more apparent and better understood by referring to the following description taken in conjunction with the accompanying drawings, in which: 
         FIG. 1A  is a block diagram of an embodiment of a network environment for a client to access a server via an appliance; 
         FIG. 1B  is a block diagram of an embodiment of an environment for delivering a computing environment from a server to a client via an appliance; 
         FIG. 1C  is a block diagram of another embodiment of an environment for delivering a computing environment from a server to a client via an appliance; 
         FIG. 1D  is a block diagram of another embodiment of an environment for delivering a computing environment from a server to a client via an appliance; 
         FIGS. 1E-1H  are block diagrams of embodiments of a computing device; 
         FIG. 2A  is a block diagram of an embodiment of an appliance for processing communications between a client and a server; 
         FIG. 2B  is a block diagram of another embodiment of an appliance for optimizing, accelerating, load-balancing and routing communications between a client and a server; 
         FIG. 3  is a block diagram of an embodiment of a client for communicating with a server via the appliance; 
         FIG. 4A  is a block diagram of an embodiment of a virtualization environment; 
         FIG. 4B  is a block diagram of another embodiment of a virtualization environment; 
         FIG. 4C  is a block diagram of an embodiment of a virtualized appliance; 
         FIG. 5A  are block diagrams of embodiments of approaches to implementing parallelism in a multi-core system; 
         FIG. 5B  is a block diagram of an embodiment of a system utilizing a multi-core system; 
         FIG. 5C  is a block diagram of another embodiment of an aspect of a multi-core system; 
         FIG. 6  is a block diagram of an embodiment of a cluster system; 
         FIG. 7A  is a block diagram of an embodiment of SNMP caching in a multi-core system; 
         FIG. 7B  is a block diagram of an embodiment of SNMP caching in a cluster system; 
         FIG. 7C  is a block diagram of an embodiment of an SNMP cache; and 
         FIG. 7D  is a flow diagram of an embodiment of a method of SNMP caching. 
     
    
    
     The features and advantages of the present invention will become more apparent from the detailed description set forth below when taken in conjunction with the drawings, in which like reference characters identify corresponding elements throughout. In the drawings, like reference numbers generally indicate identical, functionally similar, and/or structurally similar elements. 
     DETAILED DESCRIPTION OF THE INVENTION 
     For purposes of reading the description of the various embodiments below, the following descriptions of the sections of the specification and their respective contents may be helpful:
         Section A describes a network environment and computing environment which may be useful for practicing embodiments described herein;   Section B describes embodiments of systems and methods for delivering a computing environment to a remote user;   Section C describes embodiments of systems and methods for accelerating communications between a client and a server;   Section D describes embodiments of systems and methods for virtualizing an application delivery controller;   Section E describes embodiments of systems and methods for providing a multi-core architecture and environment;   Section F describes embodiments of systems and methods for providing a clustered appliance architecture environment;   Section G describes embodiments of systems and methods for SNMP caching in multi-core and clustered systems.       

     A. Network and Computing Environment 
     Prior to discussing the specifics of embodiments of the systems and methods of an appliance and/or client, it may be helpful to discuss the network and computing environments in which such embodiments may be deployed. Referring now to  FIG. 1A , an embodiment of a network environment is depicted. In brief overview, the network environment comprises one or more clients  102   a - 102   n  (also generally referred to as local machine(s)  102 , or client(s)  102 ) in communication with one or more servers  106   a - 106   n  (also generally referred to as server(s)  106 , or remote machine(s)  106 ) via one or more networks  104 ,  104 ′ (generally referred to as network  104 ). In some embodiments, a client  102  communicates with a server  106  via an appliance  200 . 
     Although  FIG. 1A  shows a network  104  and a network  104 ′ between the clients  102  and the servers  106 , the clients  102  and the servers  106  may be on the same network  104 . The networks  104  and  104 ′ can be the same type of network or different types of networks. The network  104  and/or the network  104 ′ can be a local-area network (LAN), such as a company Intranet, a metropolitan area network (MAN), or a wide area network (WAN), such as the Internet or the World Wide Web. In one embodiment, network  104 ′ may be a private network and network  104  may be a public network. In some embodiments, network  104  may be a private network and network  104 ′ a public network. In another embodiment, networks  104  and  104 ′ may both be private networks. In some embodiments, clients  102  may be located at a branch office of a corporate enterprise communicating via a WAN connection over the network  104  to the servers  106  located at a corporate data center. 
     The network  104  and/or  104 ′ be any type and/or form of network and may include any of the following: a point to point network, a broadcast network, a wide area network, a local area network, a telecommunications network, a data communication network, a computer network, an ATM (Asynchronous Transfer Mode) network, a SONET (Synchronous Optical Network) network, a SDH (Synchronous Digital Hierarchy) network, a wireless network and a wireline network. In some embodiments, the network  104  may comprise a wireless link, such as an infrared channel or satellite band. The topology of the network  104  and/or  104 ′ may be a bus, star, or ring network topology. The network  104  and/or  104 ′ and network topology may be of any such network or network topology as known to those ordinarily skilled in the art capable of supporting the operations described herein. 
     As shown in  FIG. 1A , the appliance  200 , which also may be referred to as an interface unit  200  or gateway  200 , is shown between the networks  104  and  104 ′. In some embodiments, the appliance  200  may be located on network  104 . For example, a branch office of a corporate enterprise may deploy an appliance  200  at the branch office. In other embodiments, the appliance  200  may be located on network  104 ′. For example, an appliance  200  may be located at a corporate data center. In yet another embodiment, a plurality of appliances  200  may be deployed on network  104 . In some embodiments, a plurality of appliances  200  may be deployed on network  104 ′. In one embodiment, a first appliance  200  communicates with a second appliance  200 ′. In other embodiments, the appliance  200  could be a part of any client  102  or server  106  on the same or different network  104 , 104 ′ as the client  102 . One or more appliances  200  may be located at any point in the network or network communications path between a client  102  and a server  106 . 
     In some embodiments, the appliance  200  comprises any of the network devices manufactured by Citrix Systems, Inc. of Ft. Lauderdale Fla., referred to as Citrix NetScaler devices. In other embodiments, the appliance  200  includes any of the product embodiments referred to as WebAccelerator and BigIP manufactured by F5 Networks, Inc. of Seattle, Wash. In another embodiment, the appliance  205  includes any of the DX acceleration device platforms and/or the SSL VPN series of devices, such as SA 700, SA 2000, SA 4000, and SA 6000 devices manufactured by Juniper Networks, Inc. of Sunnyvale, Calif. In yet another embodiment, the appliance  200  includes any application acceleration and/or security related appliances and/or software manufactured by Cisco Systems, Inc. of San Jose, Calif., such as the Cisco ACE Application Control Engine Module service software and network modules, and Cisco AVS Series Application Velocity System. 
     In one embodiment, the system may include multiple, logically-grouped servers  106 . In these embodiments, the logical group of servers may be referred to as a server farm  38 . In some of these embodiments, the serves  106  may be geographically dispersed. In some cases, a farm  38  may be administered as a single entity. In other embodiments, the server farm  38  comprises a plurality of server farms  38 . In one embodiment, the server farm executes one or more applications on behalf of one or more clients  102 . 
     The servers  106  within each farm  38  can be heterogeneous. One or more of the servers  106  can operate according to one type of operating system platform (e.g., WINDOWS NT, manufactured by Microsoft Corp. of Redmond, Wash.), while one or more of the other servers  106  can operate on according to another type of operating system platform (e.g., Unix or Linux). The servers  106  of each farm  38  do not need to be physically proximate to another server  106  in the same farm  38 . Thus, the group of servers  106  logically grouped as a farm  38  may be interconnected using a wide-area network (WAN) connection or medium-area network (MAN) connection. For example, a farm  38  may include servers  106  physically located in different continents or different regions of a continent, country, state, city, campus, or room. Data transmission speeds between servers  106  in the farm  38  can be increased if the servers  106  are connected using a local-area network (LAN) connection or some form of direct connection. 
     Servers  106  may be referred to as a file server, application server, web server, proxy server, or gateway server. In some embodiments, a server  106  may have the capacity to function as either an application server or as a master application server. In one embodiment, a server  106  may include an Active Directory. The clients  102  may also be referred to as client nodes or endpoints. In some embodiments, a client  102  has the capacity to function as both a client node seeking access to applications on a server and as an application server providing access to hosted applications for other clients  102   a - 102   n.    
     In some embodiments, a client  102  communicates with a server  106 . In one embodiment, the client  102  communicates directly with one of the servers  106  in a farm  38 . In another embodiment, the client  102  executes a program neighborhood application to communicate with a server  106  in a farm  38 . In still another embodiment, the server  106  provides the functionality of a master node. In some embodiments, the client  102  communicates with the server  106  in the farm  38  through a network  104 . Over the network  104 , the client  102  can, for example, request execution of various applications hosted by the servers  106   a - 106   n  in the farm  38  and receive output of the results of the application execution for display. In some embodiments, only the master node provides the functionality required to identify and provide address information associated with a server  106 ′ hosting a requested application. 
     In one embodiment, the server  106  provides functionality of a web server. In another embodiment, the server  106   a  receives requests from the client  102 , forwards the requests to a second server  106   b  and responds to the request by the client  102  with a response to the request from the server  106   b . In still another embodiment, the server  106  acquires an enumeration of applications available to the client  102  and address information associated with a server  106  hosting an application identified by the enumeration of applications. In yet another embodiment, the server  106  presents the response to the request to the client  102  using a web interface. In one embodiment, the client  102  communicates directly with the server  106  to access the identified application. In another embodiment, the client  102  receives application output data, such as display data, generated by an execution of the identified application on the server  106 . 
     Referring now to  FIG. 1B , an embodiment of a network environment deploying multiple appliances  200  is depicted. A first appliance  200  may be deployed on a first network  104  and a second appliance  200 ′ on a second network  104 ′. For example a corporate enterprise may deploy a first appliance  200  at a branch office and a second appliance  200 ′ at a data center. In another embodiment, the first appliance  200  and second appliance  200 ′ are deployed on the same network  104  or network  104 . For example, a first appliance  200  may be deployed for a first server farm  38 , and a second appliance  200  may be deployed for a second server farm  38 ′. In another example, a first appliance  200  may be deployed at a first branch office while the second appliance  200 ′ is deployed at a second branch office&#39;. In some embodiments, the first appliance  200  and second appliance  200 ′ work in cooperation or in conjunction with each other to accelerate network traffic or the delivery of application and data between a client and a server 
     Referring now to  FIG. 1C , another embodiment of a network environment deploying the appliance  200  with one or more other types of appliances, such as between one or more WAN optimization appliance  205 ,  205 ′ is depicted. For example a first WAN optimization appliance  205  is shown between networks  104  and  104 ′ and a second WAN optimization appliance  205 ′ may be deployed between the appliance  200  and one or more servers  106 . By way of example, a corporate enterprise may deploy a first WAN optimization appliance  205  at a branch office and a second WAN optimization appliance  205 ′ at a data center. In some embodiments, the appliance  205  may be located on network  104 ′. In other embodiments, the appliance  205 ′ may be located on network  104 . In some embodiments, the appliance  205 ′ may be located on network  104 ′ or network  104 ″. In one embodiment, the appliance  205  and  205 ′ are on the same network. In another embodiment, the appliance  205  and  205 ′ are on different networks. In another example, a first WAN optimization appliance  205  may be deployed for a first server farm  38  and a second WAN optimization appliance  205 ′ for a second server farm  38 ′ 
     In one embodiment, the appliance  205  is a device for accelerating, optimizing or otherwise improving the performance, operation, or quality of service of any type and form of network traffic, such as traffic to and/or from a WAN connection. In some embodiments, the appliance  205  is a performance enhancing proxy. In other embodiments, the appliance  205  is any type and form of WAN optimization or acceleration device, sometimes also referred to as a WAN optimization controller. In one embodiment, the appliance  205  is any of the product embodiments referred to as WANScaler manufactured by Citrix Systems, Inc. of Ft. Lauderdale, Fla. In other embodiments, the appliance  205  includes any of the product embodiments referred to as BIG-IP link controller and WANjet manufactured by F5 Networks, Inc. of Seattle, Wash. In another embodiment, the appliance  205  includes any of the WX and WXC WAN acceleration device platforms manufactured by Juniper Networks, Inc. of Sunnyvale, Calif. In some embodiments, the appliance  205  includes any of the steelhead line of WAN optimization appliances manufactured by Riverbed Technology of San Francisco, Calif. In other embodiments, the appliance  205  includes any of the WAN related devices manufactured by Expand Networks Inc. of Roseland, N.J. In one embodiment, the appliance  205  includes any of the WAN related appliances manufactured by Packeteer Inc. of Cupertino, California, such as the PacketShaper, iShared, and SkyX product embodiments provided by Packeteer. In yet another embodiment, the appliance  205  includes any WAN related appliances and/or software manufactured by Cisco Systems, Inc. of San Jose, Calif., such as the Cisco Wide Area Network Application Services software and network modules, and Wide Area Network engine appliances. 
     In one embodiment, the appliance  205  provides application and data acceleration services for branch-office or remote offices. In one embodiment, the appliance  205  includes optimization of Wide Area File Services (WAFS). In another embodiment, the appliance  205  accelerates the delivery of files, such as via the Common Internet File System (CIFS) protocol. In other embodiments, the appliance  205  provides caching in memory and/or storage to accelerate delivery of applications and data. In one embodiment, the appliance  205  provides compression of network traffic at any level of the network stack or at any protocol or network layer. In another embodiment, the appliance  205  provides transport layer protocol optimizations, flow control, performance enhancements or modifications and/or management to accelerate delivery of applications and data over a WAN connection. For example, in one embodiment, the appliance  205  provides Transport Control Protocol (TCP) optimizations. In other embodiments, the appliance  205  provides optimizations, flow control, performance enhancements or modifications and/or management for any session or application layer protocol. 
     In another embodiment, the appliance  205  encoded any type and form of data or information into custom or standard TCP and/or IP header fields or option fields of network packet to announce presence, functionality or capability to another appliance  205 ′. In another embodiment, an appliance  205 ′ may communicate with another appliance  205 ′ using data encoded in both TCP and/or IP header fields or options. For example, the appliance may use TCP option(s) or IP header fields or options to communicate one or more parameters to be used by the appliances  205 ,  205 ′ in performing functionality, such as WAN acceleration, or for working in conjunction with each other. 
     In some embodiments, the appliance  200  preserves any of the information encoded in TCP and/or IP header and/or option fields communicated between appliances  205  and  205 ′. For example, the appliance  200  may terminate a transport layer connection traversing the appliance  200 , such as a transport layer connection from between a client and a server traversing appliances  205  and  205 ′. In one embodiment, the appliance  200  identifies and preserves any encoded information in a transport layer packet transmitted by a first appliance  205  via a first transport layer connection and communicates a transport layer packet with the encoded information to a second appliance  205 ′ via a second transport layer connection. 
     Referring now to  FIG. 1D , a network environment for delivering and/or operating a computing environment on a client  102  is depicted. In some embodiments, a server  106  includes an application delivery system  190  for delivering a computing environment or an application and/or data file to one or more clients  102 . In brief overview, a client  10  is in communication with a server  106  via network  104 ,  104 ′ and appliance  200 . For example, the client  102  may reside in a remote office of a company, e.g., a branch office, and the server  106  may reside at a corporate data center. The client  102  comprises a client agent  120 , and a computing environment  15 . The computing environment  15  may execute or operate an application that accesses, processes or uses a data file. The computing environment  15 , application and/or data file may be delivered via the appliance  200  and/or the server  106 . 
     In some embodiments, the appliance  200  accelerates delivery of a computing environment  15 , or any portion thereof, to a client  102 . In one embodiment, the appliance  200  accelerates the delivery of the computing environment  15  by the application delivery system  190 . For example, the embodiments described herein may be used to accelerate delivery of a streaming application and data file processable by the application from a central corporate data center to a remote user location, such as a branch office of the company. In another embodiment, the appliance  200  accelerates transport layer traffic between a client  102  and a server  106 . The appliance  200  may provide acceleration techniques for accelerating any transport layer payload from a server  106  to a client  102 , such as: 1) transport layer connection pooling, 2) transport layer connection multiplexing, 3) transport control protocol buffering, 4) compression and 5) caching. In some embodiments, the appliance  200  provides load balancing of servers  106  in responding to requests from clients  102 . In other embodiments, the appliance  200  acts as a proxy or access server to provide access to the one or more servers  106 . In another embodiment, the appliance  200  provides a secure virtual private network connection from a first network  104  of the client  102  to the second network  104 ′ of the server  106 , such as an SSL VPN connection. It yet other embodiments, the appliance  200  provides application firewall security, control and management of the connection and communications between a client  102  and a server  106 . 
     In some embodiments, the application delivery management system  190  provides application delivery techniques to deliver a computing environment to a desktop of a user, remote or otherwise, based on a plurality of execution methods and based on any authentication and authorization policies applied via a policy engine  195 . With these techniques, a remote user may obtain a computing environment and access to server stored applications and data files from any network connected device  100 . In one embodiment, the application delivery system  190  may reside or execute on a server  106 . In another embodiment, the application delivery system  190  may reside or execute on a plurality of servers  106   a - 106   n . In some embodiments, the application delivery system  190  may execute in a server farm  38 . In one embodiment, the server  106  executing the application delivery system  190  may also store or provide the application and data file. In another embodiment, a first set of one or more servers  106  may execute the application delivery system  190 , and a different server  106   n  may store or provide the application and data file. In some embodiments, each of the application delivery system  190 , the application, and data file may reside or be located on different servers. In yet another embodiment, any portion of the application delivery system  190  may reside, execute or be stored on or distributed to the appliance  200 , or a plurality of appliances. 
     The client  102  may include a computing environment  15  for executing an application that uses or processes a data file. The client  102  via networks  104 ,  104 ′ and appliance  200  may request an application and data file from the server  106 . In one embodiment, the appliance  200  may forward a request from the client  102  to the server  106 . For example, the client  102  may not have the application and data file stored or accessible locally. In response to the request, the application delivery system  190  and/or server  106  may deliver the application and data file to the client  102 . For example, in one embodiment, the server  106  may transmit the application as an application stream to operate in computing environment  15  on client  102 . 
     In some embodiments, the application delivery system  190  comprises any portion of the Citrix Access Suite™ by Citrix Systems, Inc., such as the MetaFrame or Citrix Presentation Server™ and/or any of the Microsoft® Windows Terminal Services manufactured by the Microsoft Corporation. In one embodiment, the application delivery system  190  may deliver one or more applications to clients  102  or users via a remote-display protocol or otherwise via remote-based or server-based computing. In another embodiment, the application delivery system  190  may deliver one or more applications to clients or users via steaming of the application. 
     In one embodiment, the application delivery system  190  includes a policy engine  195  for controlling and managing the access to, selection of application execution methods and the delivery of applications. In some embodiments, the policy engine  195  determines the one or more applications a user or client  102  may access. In another embodiment, the policy engine  195  determines how the application should be delivered to the user or client  102 , e.g., the method of execution. In some embodiments, the application delivery system  190  provides a plurality of delivery techniques from which to select a method of application execution, such as a server-based computing, streaming or delivering the application locally to the client  120  for local execution. 
     In one embodiment, a client  102  requests execution of an application program and the application delivery system  190  comprising a server  106  selects a method of executing the application program. In some embodiments, the server  106  receives credentials from the client  102 . In another embodiment, the server  106  receives a request for an enumeration of available applications from the client  102 . In one embodiment, in response to the request or receipt of credentials, the application delivery system  190  enumerates a plurality of application programs available to the client  102 . The application delivery system  190  receives a request to execute an enumerated application. The application delivery system  190  selects one of a predetermined number of methods for executing the enumerated application, for example, responsive to a policy of a policy engine. The application delivery system  190  may select a method of execution of the application enabling the client  102  to receive application-output data generated by execution of the application program on a server  106 . The application delivery system  190  may select a method of execution of the application enabling the local machine  10  to execute the application program locally after retrieving a plurality of application files comprising the application. In yet another embodiment, the application delivery system  190  may select a method of execution of the application to stream the application via the network  104  to the client  102 . 
     A client  102  may execute, operate or otherwise provide an application, which can be any type and/or form of software, program, or executable instructions such as any type and/or form of web browser, web-based client, client-server application, a thin-client computing client, an ActiveX control, or a Java applet, or any other type and/or form of executable instructions capable of executing on client  102 . In some embodiments, the application may be a server-based or a remote-based application executed on behalf of the client  102  on a server  106 . In one embodiments the server  106  may display output to the client  102  using any thin-client or remote-display protocol, such as the Independent Computing Architecture (ICA) protocol manufactured by Citrix Systems, Inc. of Ft. Lauderdale, Fla. or the Remote Desktop Protocol (RDP) manufactured by the Microsoft Corporation of Redmond, Wash. The application can use any type of protocol and it can be, for example, an HTTP client, an FTP client, an Oscar client, or a Telnet client. In other embodiments, the application comprises any type of software related to VoIP communications, such as a soft IP telephone. In further embodiments, the application comprises any application related to real-time data communications, such as applications for streaming video and/or audio. 
     In some embodiments, the server  106  or a server farm  38  may be running one or more applications, such as an application providing a thin-client computing or remote display presentation application. In one embodiment, the server  106  or server farm  38  executes as an application, any portion of the Citrix Access Suite™ by Citrix Systems, Inc., such as the MetaFrame or Citrix Presentation Server™, and/or any of the Microsoft® Windows Terminal Services manufactured by the Microsoft Corporation. In one embodiment, the application is an ICA client, developed by Citrix Systems, Inc. of Fort Lauderdale, Fla. In other embodiments, the application includes a Remote Desktop (RDP) client, developed by Microsoft Corporation of Redmond, Wash. Also, the server  106  may run an application, which for example, may be an application server providing email services such as Microsoft Exchange manufactured by the Microsoft Corporation of Redmond, Wash., a web or Internet server, or a desktop sharing server, or a collaboration server. In some embodiments, any of the applications may comprise any type of hosted service or products, such as GoToMeeting™ provided by Citrix Online Division, Inc. of Santa Barbara, Calif., WebEx™ provided by WebEx, Inc. of Santa Clara, Calif., or Microsoft Office Live Meeting provided by Microsoft Corporation of Redmond, Wash. 
     Still referring to  FIG. 1D , an embodiment of the network environment may include a monitoring server  106 A. The monitoring server  106 A may include any type and form performance monitoring service  198 . The performance monitoring service  198  may include monitoring, measurement and/or management software and/or hardware, including data collection, aggregation, analysis, management and reporting. In one embodiment, the performance monitoring service  198  includes one or more monitoring agents  197 . The monitoring agent  197  includes any software, hardware or combination thereof for performing monitoring, measurement and data collection activities on a device, such as a client  102 , server  106  or an appliance  200 ,  205 . In some embodiments, the monitoring agent  197  includes any type and form of script, such as Visual Basic script, or Javascript. In one embodiment, the monitoring agent  197  executes transparently to any application and/or user of the device. In some embodiments, the monitoring agent  197  is installed and operated unobtrusively to the application or client. In yet another embodiment, the monitoring agent  197  is installed and operated without any instrumentation for the application or device. 
     In some embodiments, the monitoring agent  197  monitors, measures and collects data on a predetermined frequency. In other embodiments, the monitoring agent  197  monitors, measures and collects data based upon detection of any type and form of event. For example, the monitoring agent  197  may collect data upon detection of a request for a web page or receipt of an HTTP response. In another example, the monitoring agent  197  may collect data upon detection of any user input events, such as a mouse click. The monitoring agent  197  may report or provide any monitored, measured or collected data to the monitoring service  198 . In one embodiment, the monitoring agent  197  transmits information to the monitoring service  198  according to a schedule or a predetermined frequency. In another embodiment, the monitoring agent  197  transmits information to the monitoring service  198  upon detection of an event. 
     In some embodiments, the monitoring service  198  and/or monitoring agent  197  performs monitoring and performance measurement of any network resource or network infrastructure element, such as a client, server, server farm, appliance  200 , appliance  205 , or network connection. In one embodiment, the monitoring service  198  and/or monitoring agent  197  performs monitoring and performance measurement of any transport layer connection, such as a TCP or UDP connection. In another embodiment, the monitoring service  198  and/or monitoring agent  197  monitors and measures network latency. In yet one embodiment, the monitoring service  198  and/or monitoring agent  197  monitors and measures bandwidth utilization. 
     In other embodiments, the monitoring service  198  and/or monitoring agent  197  monitors and measures end-user response times. In some embodiments, the monitoring service  198  performs monitoring and performance measurement of an application. In another embodiment, the monitoring service  198  and/or monitoring agent  197  performs monitoring and performance measurement of any session or connection to the application. In one embodiment, the monitoring service  198  and/or monitoring agent  197  monitors and measures performance of a browser. In another embodiment, the monitoring service  198  and/or monitoring agent  197  monitors and measures performance of HTTP based transactions. In some embodiments, the monitoring service  198  and/or monitoring agent  197  monitors and measures performance of a Voice over IP (VoIP) application or session. In other embodiments, the monitoring service  198  and/or monitoring agent  197  monitors and measures performance of a remote display protocol application, such as an ICA client or RDP client. In yet another embodiment, the monitoring service  198  and/or monitoring agent  197  monitors and measures performance of any type and form of streaming media. In still a further embodiment, the monitoring service  198  and/or monitoring agent  197  monitors and measures performance of a hosted application or a Software-As-A-Service (SaaS) delivery model. 
     In some embodiments, the monitoring service  198  and/or monitoring agent  197  performs monitoring and performance measurement of one or more transactions, requests or responses related to application. In other embodiments, the monitoring service  198  and/or monitoring agent  197  monitors and measures any portion of an application layer stack, such as any .NET or J2EE calls. In one embodiment, the monitoring service  198  and/or monitoring agent  197  monitors and measures database or SQL transactions. In yet another embodiment, the monitoring service  198  and/or monitoring agent  197  monitors and measures any method, function or application programming interface (API) call. 
     In one embodiment, the monitoring service  198  and/or monitoring agent  197  performs monitoring and performance measurement of a delivery of application and/or data from a server to a client via one or more appliances, such as appliance  200  and/or appliance  205 . In some embodiments, the monitoring service  198  and/or monitoring agent  197  monitors and measures performance of delivery of a virtualized application. In other embodiments, the monitoring service  198  and/or monitoring agent  197  monitors and measures performance of delivery of a streaming application. In another embodiment, the monitoring service  198  and/or monitoring agent  197  monitors and measures performance of delivery of a desktop application to a client and/or the execution of the desktop application on the client. In another embodiment, the monitoring service  198  and/or monitoring agent  197  monitors and measures performance of a client/server application. 
     In one embodiment, the monitoring service  198  and/or monitoring agent  197  is designed and constructed to provide application performance management for the application delivery system  190 . For example, the monitoring service  198  and/or monitoring agent  197  may monitor, measure and manage the performance of the delivery of applications via the Citrix Presentation Server. In this example, the monitoring service  198  and/or monitoring agent  197  monitors individual ICA sessions. The monitoring service  198  and/or monitoring agent  197  may measure the total and per session system resource usage, as well as application and networking performance. The monitoring service  198  and/or monitoring agent  197  may identify the active servers for a given user and/or user session. In some embodiments, the monitoring service  198  and/or monitoring agent  197  monitors back-end connections between the application delivery system  190  and an application and/or database server. The monitoring service  198  and/or monitoring agent  197  may measure network latency, delay and volume per user-session or ICA session. 
     In some embodiments, the monitoring service  198  and/or monitoring agent  197  measures and monitors memory usage for the application delivery system  190 , such as total memory usage, per user session and/or per process. In other embodiments, the monitoring service  198  and/or monitoring agent  197  measures and monitors CPU usage the application delivery system  190 , such as total CPU usage, per user session and/or per process. In another embodiments, the monitoring service  198  and/or monitoring agent  197  measures and monitors the time required to log-in to an application, a server, or the application delivery system, such as Citrix Presentation Server. In one embodiment, the monitoring service  198  and/or monitoring agent  197  measures and monitors the duration a user is logged into an application, a server, or the application delivery system  190 . In some embodiments, the monitoring service  198  and/or monitoring agent  197  measures and monitors active and inactive session counts for an application, server or application delivery system session. In yet another embodiment, the monitoring service  198  and/or monitoring agent  197  measures and monitors user session latency. 
     In yet further embodiments, the monitoring service  198  and/or monitoring agent  197  measures and monitors measures and monitors any type and form of server metrics. In one embodiment, the monitoring service  198  and/or monitoring agent  197  measures and monitors metrics related to system memory, CPU usage, and disk storage. In another embodiment, the monitoring service  198  and/or monitoring agent  197  measures and monitors metrics related to page faults, such as page faults per second. In other embodiments, the monitoring service  198  and/or monitoring agent  197  measures and monitors round-trip time metrics. In yet another embodiment, the monitoring service  198  and/or monitoring agent  197  measures and monitors metrics related to application crashes, errors and/or hangs. 
     In some embodiments, the monitoring service  198  and monitoring agent  198  includes any of the product embodiments referred to as EdgeSight manufactured by Citrix Systems, Inc. of Ft. Lauderdale, Fla. In another embodiment, the performance monitoring service  198  and/or monitoring agent  198  includes any portion of the product embodiments referred to as the TrueView product suite manufactured by the Symphoniq Corporation of Palo Alto, Calif. In one embodiment, the performance monitoring service  198  and/or monitoring agent  198  includes any portion of the product embodiments referred to as the TeaLeaf CX product suite manufactured by the TeaLeaf Technology Inc. of San Francisco, Calif. In other embodiments, the performance monitoring service  198  and/or monitoring agent  198  includes any portion of the business service management products, such as the BMC Performance Manager and Patrol products, manufactured by BMC Software, Inc. of Houston, Tex. 
     The client  102 , server  106 , and appliance  200  may be deployed as and/or executed on any type and form of computing device, such as a computer, network device or appliance capable of communicating on any type and form of network and performing the operations described herein.  FIGS. 1E and 1F  depict block diagrams of a computing device  100  useful for practicing an embodiment of the client  102 , server  106  or appliance  200 . As shown in  FIGS. 1E and 1F , each computing device  100  includes a central processing unit  101 , and a main memory unit  122 . As shown in  FIG. 1E , a computing device  100  may include a visual display device  124 , a keyboard  126  and/or a pointing device  127 , such as a mouse. Each computing device  100  may also include additional optional elements, such as one or more input/output devices  130   a - 130   b  (generally referred to using reference numeral  130 ), and a cache memory  140  in communication with the central processing unit  101 . 
     The central processing unit  101  is any logic circuitry that responds to and processes instructions fetched from the main memory unit  122 . In many embodiments, the central processing unit is provided by a microprocessor unit, such as: those manufactured by Intel Corporation of Mountain View, Calif.; those manufactured by Motorola Corporation of Schaumburg, Ill.; those manufactured by Transmeta Corporation of Santa Clara, California; the RS/6000 processor, those manufactured by International Business Machines of White Plains, N.Y.; or those manufactured by Advanced Micro Devices of Sunnyvale, Calif. The computing device  100  may be based on any of these processors, or any other processor capable of operating as described herein. 
     Main memory unit  122  may be one or more memory chips capable of storing data and allowing any storage location to be directly accessed by the microprocessor  101 , such as Static random access memory (SRAM), Burst SRAM or SynchBurst SRAM (BSRAM), Dynamic random access memory (DRAM), Fast Page Mode DRAM (FPM DRAM), Enhanced DRAM (EDRAM), Extended Data Output RAM (EDO RAM), Extended Data Output DRAM (EDO DRAM), Burst Extended Data Output DRAM (BEDO DRAM), Enhanced DRAM (EDRAM), synchronous DRAM (SDRAM), JEDEC SRAM, PC100 SDRAM, Double Data Rate SDRAM (DDR SDRAM), Enhanced SDRAM (ESDRAM), SyncLink DRAM (SLDRAM), Direct Rambus DRAM (DRDRAM), or Ferroelectric RAM (FRAM). The main memory  122  may be based on any of the above described memory chips, or any other available memory chips capable of operating as described herein. In the embodiment shown in  FIG. 1E , the processor  101  communicates with main memory  122  via a system bus  150  (described in more detail below).  FIG. 1F  depicts an embodiment of a computing device  100  in which the processor communicates directly with main memory  122  via a memory port  103 . For example, in  FIG. 1F  the main memory  122  may be DRDRAM. 
       FIG. 1F  depicts an embodiment in which the main processor  101  communicates directly with cache memory  140  via a secondary bus, sometimes referred to as a backside bus. In other embodiments, the main processor  101  communicates with cache memory  140  using the system bus  150 . Cache memory  140  typically has a faster response time than main memory  122  and is typically provided by SRAM, BSRAM, or EDRAM. In the embodiment shown in  FIG. 1F , the processor  101  communicates with various I/O devices  130  via a local system bus  150 . Various busses may be used to connect the central processing unit  101  to any of the I/O devices  130 , including a VESA VL bus, an ISA bus, an EISA bus, a MicroChannel Architecture (MCA) bus, a PCI bus, a PCI-X bus, a PCI-Express bus, or a NuBus. For embodiments in which the I/O device is a video display  124 , the processor  101  may use an Advanced Graphics Port (AGP) to communicate with the display  124 .  FIG. 1F  depicts an embodiment of a computer  100  in which the main processor  101  communicates directly with I/O device  130   b  via HyperTransport, Rapid I/O, or InfiniBand.  FIG. 1F  also depicts an embodiment in which local busses and direct communication are mixed: the processor  101  communicates with I/O device  130   b  using a local interconnect bus while communicating with I/O device  130   a  directly. 
     The computing device  100  may support any suitable installation device  116 , such as a floppy disk drive for receiving floppy disks such as 3.5-inch, 5.25-inch disks or ZIP disks, a CD-ROM drive, a CD-R/RW drive, a DVD-ROM drive, tape drives of various formats, USB device, hard-drive or any other device suitable for installing software and programs such as any client agent  120 , or portion thereof. The computing device  100  may further comprise a storage device  128 , such as one or more hard disk drives or redundant arrays of independent disks, for storing an operating system and other related software, and for storing application software programs such as any program related to the client agent  120 . Optionally, any of the installation devices  116  could also be used as the storage device  128 . Additionally, the operating system and the software can be run from a bootable medium, for example, a bootable CD, such as KNOPPIX®, a bootable CD for GNU/Linux that is available as a GNU/Linux distribution from knoppix.net. 
     Furthermore, the computing device  100  may include a network interface  118  to interface to a Local Area Network (LAN), Wide Area Network (WAN) or the Internet through a variety of connections including, but not limited to, standard telephone lines, LAN or WAN links (e.g., 802.11, T1, T3, 56 kb, X.25), broadband connections (e.g., ISDN, Frame Relay, ATM), wireless connections, or some combination of any or all of the above. The network interface  118  may comprise a built-in network adapter, network interface card, PCMCIA network card, card bus network adapter, wireless network adapter, USB network adapter, modem or any other device suitable for interfacing the computing device  100  to any type of network capable of communication and performing the operations described herein. A wide variety of I/O devices  130   a - 130   n  may be present in the computing device  100 . Input devices include keyboards, mice, trackpads, trackballs, microphones, and drawing tablets. Output devices include video displays, speakers, inkjet printers, laser printers, and dye-sublimation printers. The I/O devices  130  may be controlled by an I/O controller  123  as shown in  FIG. 1E . The I/O controller may control one or more I/O devices such as a keyboard  126  and a pointing device  127 , e.g., a mouse or optical pen. Furthermore, an I/O device may also provide storage  128  and/or an installation medium  116  for the computing device  100 . In still other embodiments, the computing device  100  may provide USB connections to receive handheld USB storage devices such as the USB Flash Drive line of devices manufactured by Twintech Industry, Inc. of Los Alamitos, Calif. 
     In some embodiments, the computing device  100  may comprise or be connected to multiple display devices  124   a - 124   n , which each may be of the same or different type and/or form. As such, any of the I/O devices  130   a - 130   n  and/or the I/O controller  123  may comprise any type and/or form of suitable hardware, software, or combination of hardware and software to support, enable or provide for the connection and use of multiple display devices  124   a - 124   n  by the computing device  100 . For example, the computing device  100  may include any type and/or form of video adapter, video card, driver, and/or library to interface, communicate, connect or otherwise use the display devices  124   a - 124   n . In one embodiment, a video adapter may comprise multiple connectors to interface to multiple display devices  124   a - 124   n . In other embodiments, the computing device  100  may include multiple video adapters, with each video adapter connected to one or more of the display devices  124   a - 124   n . In some embodiments, any portion of the operating system of the computing device  100  may be configured for using multiple displays  124   a - 124   n . In other embodiments, one or more of the display devices  124   a - 124   n  may be provided by one or more other computing devices, such as computing devices  100   a  and  100   b  connected to the computing device  100 , for example, via a network. These embodiments may include any type of software designed and constructed to use another computer&#39;s display device as a second display device  124   a  for the computing device  100 . One ordinarily skilled in the art will recognize and appreciate the various ways and embodiments that a computing device  100  may be configured to have multiple display devices  124   a - 124   n.    
     In further embodiments, an I/O device  130  may be a bridge  170  between the system bus  150  and an external communication bus, such as a USB bus, an Apple Desktop Bus, an RS-232 serial connection, a SCSI bus, a FireWire bus, a FireWire  800  bus, an Ethernet bus, an AppleTalk bus, a Gigabit Ethernet bus, an Asynchronous Transfer Mode bus, a HIPPI bus, a Super HIPPI bus, a SerialPlus bus, a SCI/LAMP bus, a FibreChannel bus, or a Serial Attached small computer system interface bus. 
     A computing device  100  of the sort depicted in  FIGS. 1E and 1F  typically operate under the control of operating systems, which control scheduling of tasks and access to system resources. The computing device  100  can be running any operating system such as any of the versions of the Microsoft® Windows operating systems, the different releases of the Unix and Linux operating systems, any version of the Mac OS® for Macintosh computers, any embedded operating system, any real-time operating system, any open source operating system, any proprietary operating system, any operating systems for mobile computing devices, or any other operating system capable of running on the computing device and performing the operations described herein. Typical operating systems include: WINDOWS 3.x, WINDOWS 95, WINDOWS 98, WINDOWS 2000, WINDOWS NT 3.51, WINDOWS NT 4.0, WINDOWS CE, and WINDOWS XP, all of which are manufactured by Microsoft Corporation of Redmond, Wash.; MacOS, manufactured by Apple Computer of Cupertino, California; OS/2, manufactured by International Business Machines of Armonk, N.Y.; and Linux, a freely-available operating system distributed by Caldera Corp. of Salt Lake City, Utah, or any type and/or form of a Unix operating system, among others. 
     In other embodiments, the computing device  100  may have different processors, operating systems, and input devices consistent with the device. For example, in one embodiment the computer  100  is a Treo  180 ,  270 ,  1060 ,  600  or  650  smart phone manufactured by Palm, Inc. In this embodiment, the Treo smart phone is operated under the control of the PalmOS operating system and includes a stylus input device as well as a five-way navigator device. Moreover, the computing device  100  can be any workstation, desktop computer, laptop or notebook computer, server, handheld computer, mobile telephone, any other computer, or other form of computing or telecommunications device that is capable of communication and that has sufficient processor power and memory capacity to perform the operations described herein. 
     As shown in  FIG. 1G , the computing device  100  may comprise multiple processors and may provide functionality for simultaneous execution of instructions or for simultaneous execution of one instruction on more than one piece of data. In some embodiments, the computing device  100  may comprise a parallel processor with one or more cores. In one of these embodiments, the computing device  100  is a shared memory parallel device, with multiple processors and/or multiple processor cores, accessing all available memory as a single global address space. In another of these embodiments, the computing device  100  is a distributed memory parallel device with multiple processors each accessing local memory only. In still another of these embodiments, the computing device  100  has both some memory which is shared and some memory which can only be accessed by particular processors or subsets of processors. In still even another of these embodiments, the computing device  100 , such as a multi-core microprocessor, combines two or more independent processors into a single package, often a single integrated circuit (IC). In yet another of these embodiments, the computing device  100  includes a chip having a CELL BROADBAND ENGINE architecture and including a Power processor element and a plurality of synergistic processing elements, the Power processor element and the plurality of synergistic processing elements linked together by an internal high speed bus, which may be referred to as an element interconnect bus. 
     In some embodiments, the processors provide functionality for execution of a single instruction simultaneously on multiple pieces of data (SIMD). In other embodiments, the processors provide functionality for execution of multiple instructions simultaneously on multiple pieces of data (MIMD). In still other embodiments, the processor may use any combination of SIMD and MIMD cores in a single device. 
     In some embodiments, the computing device  100  may comprise a graphics processing unit. In one of these embodiments, depicted in  FIG. 1H , the computing device  100  includes at least one central processing unit  101  and at least one graphics processing unit. In another of these embodiments, the computing device  100  includes at least one parallel processing unit and at least one graphics processing unit. In still another of these embodiments, the computing device  100  includes a plurality of processing units of any type, one of the plurality of processing units comprising a graphics processing unit. 
     In some embodiments, a first computing device  100   a  executes an application on behalf of a user of a client computing device  100   b . In other embodiments, a computing device  100   a  executes a virtual machine, which provides an execution session within which applications execute on behalf of a user or a client computing devices  100   b . In one of these embodiments, the execution session is a hosted desktop session. In another of these embodiments, the computing device  100  executes a terminal services session. The terminal services session may provide a hosted desktop environment. In still another of these embodiments, the execution session provides access to a computing environment, which may comprise one or more of: an application, a plurality of applications, a desktop application, and a desktop session in which one or more applications may execute. 
     B. Appliance Architecture 
       FIG. 2A  illustrates an example embodiment of the appliance  200 . The architecture of the appliance  200  in  FIG. 2A  is provided by way of illustration only and is not intended to be limiting. As shown in  FIG. 2 , appliance  200  comprises a hardware layer  206  and a software layer divided into a user space  202  and a kernel space  204 . 
     Hardware layer  206  provides the hardware elements upon which programs and services within kernel space  204  and user space  202  are executed. Hardware layer  206  also provides the structures and elements which allow programs and services within kernel space  204  and user space  202  to communicate data both internally and externally with respect to appliance  200 . As shown in  FIG. 2 , the hardware layer  206  includes a processing unit  262  for executing software programs and services, a memory  264  for storing software and data, network ports  266  for transmitting and receiving data over a network, and an encryption processor  260  for performing functions related to Secure Sockets Layer processing of data transmitted and received over the network. In some embodiments, the central processing unit  262  may perform the functions of the encryption processor  260  in a single processor. Additionally, the hardware layer  206  may comprise multiple processors for each of the processing unit  262  and the encryption processor  260 . The processor  262  may include any of the processors  101  described above in connection with  FIGS. 1E and 1F . For example, in one embodiment, the appliance  200  comprises a first processor  262  and a second processor  262 ′. In other embodiments, the processor  262  or  262 ′ comprises a multi-core processor. 
     Although the hardware layer  206  of appliance  200  is generally illustrated with an encryption processor  260 , processor  260  may be a processor for performing functions related to any encryption protocol, such as the Secure Socket Layer (SSL) or Transport Layer Security (TLS) protocol. In some embodiments, the processor  260  may be a general purpose processor (GPP), and in further embodiments, may have executable instructions for performing processing of any security related protocol. 
     Although the hardware layer  206  of appliance  200  is illustrated with certain elements in  FIG. 2 , the hardware portions or components of appliance  200  may comprise any type and form of elements, hardware or software, of a computing device, such as the computing device  100  illustrated and discussed herein in conjunction with  FIGS. 1E and 1F . In some embodiments, the appliance  200  may comprise a server, gateway, router, switch, bridge or other type of computing or network device, and have any hardware and/or software elements associated therewith. 
     The operating system of appliance  200  allocates, manages, or otherwise segregates the available system memory into kernel space  204  and user space  204 . In example software architecture  200 , the operating system may be any type and/or form of Unix operating system although the invention is not so limited. As such, the appliance  200  can be running any operating system such as any of the versions of the Microsoft® Windows operating systems, the different releases of the Unix and Linux operating systems, any version of the Mac OS® for Macintosh computers, any embedded operating system, any network operating system, any real-time operating system, any open source operating system, any proprietary operating system, any operating systems for mobile computing devices or network devices, or any other operating system capable of running on the appliance  200  and performing the operations described herein. 
     The kernel space  204  is reserved for running the kernel  230 , including any device drivers, kernel extensions or other kernel related software. As known to those skilled in the art, the kernel  230  is the core of the operating system, and provides access, control, and management of resources and hardware-related elements of the application  104 . In accordance with an embodiment of the appliance  200 , the kernel space  204  also includes a number of network services or processes working in conjunction with a cache manager  232 , sometimes also referred to as the integrated cache, the benefits of which are described in detail further herein. Additionally, the embodiment of the kernel  230  will depend on the embodiment of the operating system installed, configured, or otherwise used by the device  200 . 
     In one embodiment, the device  200  comprises one network stack  267 , such as a TCP/IP based stack, for communicating with the client  102  and/or the server  106 . In one embodiment, the network stack  267  is used to communicate with a first network, such as network  108 , and a second network  110 . In some embodiments, the device  200  terminates a first transport layer connection, such as a TCP connection of a client  102 , and establishes a second transport layer connection to a server  106  for use by the client  102 , e.g., the second transport layer connection is terminated at the appliance  200  and the server  106 . The first and second transport layer connections may be established via a single network stack  267 . In other embodiments, the device  200  may comprise multiple network stacks, for example  267  and  267 ′, and the first transport layer connection may be established or terminated at one network stack  267 , and the second transport layer connection on the second network stack  267 ′. For example, one network stack may be for receiving and transmitting network packet on a first network, and another network stack for receiving and transmitting network packets on a second network. In one embodiment, the network stack  267  comprises a buffer  243  for queuing one or more network packets for transmission by the appliance  200 . 
     As shown in  FIG. 2 , the kernel space  204  includes the cache manager  232 , a high-speed layer 2-7 integrated packet engine  240 , an encryption engine  234 , a policy engine  236  and multi-protocol compression logic  238 . Running these components or processes  232 ,  240 ,  234 ,  236  and  238  in kernel space  204  or kernel mode instead of the user space  202  improves the performance of each of these components, alone and in combination. Kernel operation means that these components or processes  232 ,  240 ,  234 ,  236  and  238  run in the core address space of the operating system of the device  200 . For example, running the encryption engine  234  in kernel mode improves encryption performance by moving encryption and decryption operations to the kernel, thereby reducing the number of transitions between the memory space or a kernel thread in kernel mode and the memory space or a thread in user mode. For example, data obtained in kernel mode may not need to be passed or copied to a process or thread running in user mode, such as from a kernel level data structure to a user level data structure. In another aspect, the number of context switches between kernel mode and user mode are also reduced. Additionally, synchronization of and communications between any of the components or processes  232 ,  240 ,  235 ,  236  and  238  can be performed more efficiently in the kernel space  204 . 
     In some embodiments, any portion of the components  232 ,  240 ,  234 ,  236  and  238  may run or operate in the kernel space  204 , while other portions of these components  232 ,  240 ,  234 ,  236  and  238  may run or operate in user space  202 . In one embodiment, the appliance  200  uses a kernel-level data structure providing access to any portion of one or more network packets, for example, a network packet comprising a request from a client  102  or a response from a server  106 . In some embodiments, the kernel-level data structure may be obtained by the packet engine  240  via a transport layer driver interface or filter to the network stack  267 . The kernel-level data structure may comprise any interface and/or data accessible via the kernel space  204  related to the network stack  267 , network traffic or packets received or transmitted by the network stack  267 . In other embodiments, the kernel-level data structure may be used by any of the components or processes  232 ,  240 ,  234 ,  236  and  238  to perform the desired operation of the component or process. In one embodiment, a component  232 ,  240 ,  234 ,  236  and  238  is running in kernel mode  204  when using the kernel-level data structure, while in another embodiment, the component  232 ,  240 ,  234 ,  236  and  238  is running in user mode when using the kernel-level data structure. In some embodiments, the kernel-level data structure may be copied or passed to a second kernel-level data structure, or any desired user-level data structure. 
     The cache manager  232  may comprise software, hardware or any combination of software and hardware to provide cache access, control and management of any type and form of content, such as objects or dynamically generated objects served by the originating servers  106 . The data, objects or content processed and stored by the cache manager  232  may comprise data in any format, such as a markup language, or communicated via any protocol. In some embodiments, the cache manager  232  duplicates original data stored elsewhere or data previously computed, generated or transmitted, in which the original data may require longer access time to fetch, compute or otherwise obtain relative to reading a cache memory element. Once the data is stored in the cache memory element, future use can be made by accessing the cached copy rather than refetching or recomputing the original data, thereby reducing the access time. In some embodiments, the cache memory element may comprise a data object in memory  264  of device  200 . In other embodiments, the cache memory element may comprise memory having a faster access time than memory  264 . In another embodiment, the cache memory element may comprise any type and form of storage element of the device  200 , such as a portion of a hard disk. In some embodiments, the processing unit  262  may provide cache memory for use by the cache manager  232 . In yet further embodiments, the cache manager  232  may use any portion and combination of memory, storage, or the processing unit for caching data, objects, and other content. 
     Furthermore, the cache manager  232  includes any logic, functions, rules, or operations to perform any embodiments of the techniques of the appliance  200  described herein. For example, the cache manager  232  includes logic or functionality to invalidate objects based on the expiration of an invalidation time period or upon receipt of an invalidation command from a client  102  or server  106 . In some embodiments, the cache manager  232  may operate as a program, service, process or task executing in the kernel space  204 , and in other embodiments, in the user space  202 . In one embodiment, a first portion of the cache manager  232  executes in the user space  202  while a second portion executes in the kernel space  204 . In some embodiments, the cache manager  232  can comprise any type of general purpose processor (GPP), or any other type of integrated circuit, such as a Field Programmable Gate Array (FPGA), Programmable Logic Device (PLD), or Application Specific Integrated Circuit (ASIC). 
     The policy engine  236  may include, for example, an intelligent statistical engine or other programmable application(s). In one embodiment, the policy engine  236  provides a configuration mechanism to allow a user to identify, specify, define or configure a caching policy. Policy engine  236 , in some embodiments, also has access to memory to support data structures such as lookup tables or hash tables to enable user-selected caching policy decisions. In other embodiments, the policy engine  236  may comprise any logic, rules, functions or operations to determine and provide access, control and management of objects, data or content being cached by the appliance  200  in addition to access, control and management of security, network traffic, network access, compression or any other function or operation performed by the appliance  200 . Further examples of specific caching policies are further described herein. 
     The encryption engine  234  comprises any logic, business rules, functions or operations for handling the processing of any security related protocol, such as SSL or TLS, or any function related thereto. For example, the encryption engine  234  encrypts and decrypts network packets, or any portion thereof, communicated via the appliance  200 . The encryption engine  234  may also setup or establish SSL or TLS connections on behalf of the client  102   a - 102   n , server  106   a - 106   n , or appliance  200 . As such, the encryption engine  234  provides offloading and acceleration of SSL processing. In one embodiment, the encryption engine  234  uses a tunneling protocol to provide a virtual private network between a client  102   a - 102   n  and a server  106   a - 106   n . In some embodiments, the encryption engine  234  is in communication with the Encryption processor  260 . In other embodiments, the encryption engine  234  comprises executable instructions running on the Encryption processor  260 . 
     The multi-protocol compression engine  238  comprises any logic, business rules, function or operations for compressing one or more protocols of a network packet, such as any of the protocols used by the network stack  267  of the device  200 . In one embodiment, multi-protocol compression engine  238  compresses bi-directionally between clients  102   a - 102   n  and servers  106   a - 106   n  any TCP/IP based protocol, including Messaging Application Programming Interface (MAPI) (email), File Transfer Protocol (FTP), HyperText Transfer Protocol (HTTP), Common Internet File System (CIFS) protocol (file transfer), Independent Computing Architecture (ICA) protocol, Remote Desktop Protocol (RDP), Wireless Application Protocol (WAP), Mobile IP protocol, and Voice Over IP (VoIP) protocol. In other embodiments, multi-protocol compression engine  238  provides compression of Hypertext Markup Language (HTML) based protocols and in some embodiments, provides compression of any markup languages, such as the Extensible Markup Language (XML). In one embodiment, the multi-protocol compression engine  238  provides compression of any high-performance protocol, such as any protocol designed for appliance  200  to appliance  200  communications. In another embodiment, the multi-protocol compression engine  238  compresses any payload of or any communication using a modified transport control protocol, such as Transaction TCP (T/TCP), TCP with selection acknowledgements (TCP-SACK), TCP with large windows (TCP-LW), a congestion prediction protocol such as the TCP-Vegas protocol, and a TCP spoofing protocol. 
     As such, the multi-protocol compression engine  238  accelerates performance for users accessing applications via desktop clients, e.g., Microsoft Outlook and non-Web thin clients, such as any client launched by popular enterprise applications like Oracle, SAP and Siebel, and even mobile clients, such as the Pocket PC. In some embodiments, the multi-protocol compression engine  238  by executing in the kernel mode  204  and integrating with packet processing engine  240  accessing the network stack  267  is able to compress any of the protocols carried by the TCP/IP protocol, such as any application layer protocol. 
     High speed layer 2-7 integrated packet engine  240 , also generally referred to as a packet processing engine or packet engine, is responsible for managing the kernel-level processing of packets received and transmitted by appliance  200  via network ports  266 . The high speed layer 2-7 integrated packet engine  240  may comprise a buffer for queuing one or more network packets during processing, such as for receipt of a network packet or transmission of a network packet. Additionally, the high speed layer 2-7 integrated packet engine  240  is in communication with one or more network stacks  267  to send and receive network packets via network ports  266 . The high speed layer 2-7 integrated packet engine  240  works in conjunction with encryption engine  234 , cache manager  232 , policy engine  236  and multi-protocol compression logic  238 . In particular, encryption engine  234  is configured to perform SSL processing of packets, policy engine  236  is configured to perform functions related to traffic management such as request-level content switching and request-level cache redirection, and multi-protocol compression logic  238  is configured to perform functions related to compression and decompression of data. 
     The high speed layer 2-7 integrated packet engine  240  includes a packet processing timer  242 . In one embodiment, the packet processing timer  242  provides one or more time intervals to trigger the processing of incoming, i.e., received, or outgoing, i.e., transmitted, network packets. In some embodiments, the high speed layer 2-7 integrated packet engine  240  processes network packets responsive to the timer  242 . The packet processing timer  242  provides any type and form of signal to the packet engine  240  to notify, trigger, or communicate a time related event, interval or occurrence. In many embodiments, the packet processing timer  242  operates in the order of milliseconds, such as for example 100 ms, 50 ms or 25 ms. For example, in some embodiments, the packet processing timer  242  provides time intervals or otherwise causes a network packet to be processed by the high speed layer 2-7integrated packet engine  240  at a 10 ms time interval, while in other embodiments, at a 5 ms time interval, and still yet in further embodiments, as short as a 3, 2, or 1 ms time interval. The high speed layer 2-7 integrated packet engine  240  may be interfaced, integrated or in communication with the encryption engine  234 , cache manager  232 , policy engine  236  and multi-protocol compression engine  238  during operation. As such, any of the logic, functions, or operations of the encryption engine  234 , cache manager  232 , policy engine  236  and multi-protocol compression logic  238  may be performed responsive to the packet processing timer  242  and/or the packet engine  240 . Therefore, any of the logic, functions, or operations of the encryption engine  234 , cache manager  232 , policy engine  236  and multi-protocol compression logic  238  may be performed at the granularity of time intervals provided via the packet processing timer  242 , for example, at a time interval of less than or equal to 10 ms. For example, in one embodiment, the cache manager  232  may perform invalidation of any cached objects responsive to the high speed layer 2-7 integrated packet engine  240  and/or the packet processing timer  242 . In another embodiment, the expiry or invalidation time of a cached object can be set to the same order of granularity as the time interval of the packet processing timer  242 , such as at every 10 ms. 
     In contrast to kernel space  204 , user space  202  is the memory area or portion of the operating system used by user mode applications or programs otherwise running in user mode. A user mode application may not access kernel space  204  directly and uses service calls in order to access kernel services. As shown in  FIG. 2 , user space  202  of appliance  200  includes a graphical user interface (GUI)  210 , a command line interface (CLI)  212 , shell services  214 , health monitoring program  216 , and daemon services  218 . GUI  210  and CLI  212  provide a means by which a system administrator or other user can interact with and control the operation of appliance  200 , such as via the operating system of the appliance  200 . The GUI  210  or CLI  212  can comprise code running in user space  202  or kernel space  204 . The GUI  210  may be any type and form of graphical user interface and may be presented via text, graphical or otherwise, by any type of program or application, such as a browser. The CLI  212  may be any type and form of command line or text-based interface, such as a command line provided by the operating system. For example, the CLI  212  may comprise a shell, which is a tool to enable users to interact with the operating system. In some embodiments, the CLI  212  may be provided via a bash, csh, tcsh, or ksh type shell. The shell services  214  comprises the programs, services, tasks, processes or executable instructions to support interaction with the appliance  200  or operating system by a user via the GUI  210  and/or CLI  212 . 
     Health monitoring program  216  is used to monitor, check, report and ensure that network systems are functioning properly and that users are receiving requested content over a network. Health monitoring program  216  comprises one or more programs, services, tasks, processes or executable instructions to provide logic, rules, functions or operations for monitoring any activity of the appliance  200 . In some embodiments, the health monitoring program  216  intercepts and inspects any network traffic passed via the appliance  200 . In other embodiments, the health monitoring program  216  interfaces by any suitable means and/or mechanisms with one or more of the following: the encryption engine  234 , cache manager  232 , policy engine  236 , multi-protocol compression logic  238 , packet engine  240 , daemon services  218 , and shell services  214 . As such, the health monitoring program  216  may call any application programming interface (API) to determine a state, status, or health of any portion of the appliance  200 . For example, the health monitoring program  216  may ping or send a status inquiry on a periodic basis to check if a program, process, service or task is active and currently running. In another example, the health monitoring program  216  may check any status, error or history logs provided by any program, process, service or task to determine any condition, status or error with any portion of the appliance  200 . 
     Daemon services  218  are programs that run continuously or in the background and handle periodic service requests received by appliance  200 . In some embodiments, a daemon service may forward the requests to other programs or processes, such as another daemon service  218  as appropriate. As known to those skilled in the art, a daemon service  218  may run unattended to perform continuous or periodic system wide functions, such as network control, or to perform any desired task. In some embodiments, one or more daemon services  218  run in the user space  202 , while in other embodiments, one or more daemon services  218  run in the kernel space. 
     Referring now to  FIG. 2B , another embodiment of the appliance  200  is depicted. In brief overview, the appliance  200  provides one or more of the following services, functionality or operations: SSL VPN connectivity  280 , switching/load balancing  284 , Domain Name Service resolution  286 , acceleration  288  and an application firewall  290  for communications between one or more clients  102  and one or more servers  106 . Each of the servers  106  may provide one or more network related services  270   a - 270   n  (referred to as services  270 ). For example, a server  106  may provide an http service  270 . The appliance  200  comprises one or more virtual servers or virtual internet protocol servers, referred to as a vServer, VIP server, or just VIP  275   a - 275   n  (also referred herein as vServer  275 ). The vServer  275  receives, intercepts or otherwise processes communications between a client  102  and a server  106  in accordance with the configuration and operations of the appliance  200 . 
     The vServer  275  may comprise software, hardware or any combination of software and hardware. The vServer  275  may comprise any type and form of program, service, task, process or executable instructions operating in user mode  202 , kernel mode  204  or any combination thereof in the appliance  200 . The vServer  275  includes any logic, functions, rules, or operations to perform any embodiments of the techniques described herein, such as SSL VPN  280 , switching/load balancing  284 , Domain Name Service resolution  286 , acceleration  288  and an application firewall  290 . In some embodiments, the vServer  275  establishes a connection to a service  270  of a server  106 . The service  275  may comprise any program, application, process, task or set of executable instructions capable of connecting to and communicating to the appliance  200 , client  102  or vServer  275 . For example, the service  275  may comprise a web server, http server, ftp, email or database server. In some embodiments, the service  270  is a daemon process or network driver for listening, receiving and/or sending communications for an application, such as email, database or an enterprise application. In some embodiments, the service  270  may communicate on a specific IP address, or IP address and port. 
     In some embodiments, the vServer  275  applies one or more policies of the policy engine  236  to network communications between the client  102  and server  106 . In one embodiment, the policies are associated with a vServer  275 . In another embodiment, the policies are based on a user, or a group of users. In yet another embodiment, a policy is global and applies to one or more vServers  275   a - 275   n , and any user or group of users communicating via the appliance  200 . In some embodiments, the policies of the policy engine have conditions upon which the policy is applied based on any content of the communication, such as internet protocol address, port, protocol type, header or fields in a packet, or the context of the communication, such as user, group of the user, vServer  275 , transport layer connection, and/or identification or attributes of the client  102  or server  106 . 
     In other embodiments, the appliance  200  communicates or interfaces with the policy engine  236  to determine authentication and/or authorization of a remote user or a remote client  102  to access the computing environment  15 , application, and/or data file from a server  106 . In another embodiment, the appliance  200  communicates or interfaces with the policy engine  236  to determine authentication and/or authorization of a remote user or a remote client  102  to have the application delivery system  190  deliver one or more of the computing environment  15 , application, and/or data file. In yet another embodiment, the appliance  200  establishes a VPN or SSL VPN connection based on the policy engine&#39;s  236  authentication and/or authorization of a remote user or a remote client  102  In one embodiment, the appliance  200  controls the flow of network traffic and communication sessions based on policies of the policy engine  236 . For example, the appliance  200  may control the access to a computing environment  15 , application or data file based on the policy engine  236 . 
     In some embodiments, the vServer  275  establishes a transport layer connection, such as a TCP or UDP connection with a client  102  via the client agent  120 . In one embodiment, the vServer  275  listens for and receives communications from the client  102 . In other embodiments, the vServer  275  establishes a transport layer connection, such as a TCP or UDP connection with a client server  106 . In one embodiment, the vServer  275  establishes the transport layer connection to an internet protocol address and port of a server  270  running on the server  106 . In another embodiment, the vServer  275  associates a first transport layer connection to a client  102  with a second transport layer connection to the server  106 . In some embodiments, a vServer  275  establishes a pool of transport layer connections to a server  106  and multiplexes client requests via the pooled transport layer connections. 
     In some embodiments, the appliance  200  provides a SSL VPN connection  280  between a client  102  and a server  106 . For example, a client  102  on a first network  102  requests to establish a connection to a server  106  on a second network  104 ′. In some embodiments, the second network  104 ′ is not routable from the first network  104 . In other embodiments, the client  102  is on a public network  104  and the server  106  is on a private network  104 ′, such as a corporate network. In one embodiment, the client agent  120  intercepts communications of the client  102  on the first network  104 , encrypts the communications, and transmits the communications via a first transport layer connection to the appliance  200 . The appliance  200  associates the first transport layer connection on the first network  104  to a second transport layer connection to the server  106  on the second network  104 . The appliance  200  receives the intercepted communication from the client agent  102 , decrypts the communications, and transmits the communication to the server  106  on the second network  104  via the second transport layer connection. The second transport layer connection may be a pooled transport layer connection. As such, the appliance  200  provides an end-to-end secure transport layer connection for the client  102  between the two networks  104 ,  104 ′. 
     In one embodiment, the appliance  200  hosts an intranet internet protocol or IntranetIP  282  address of the client  102  on the virtual private network  104 . The client  102  has a local network identifier, such as an internet protocol (IP) address and/or host name on the first network  104 . When connected to the second network  104 ′ via the appliance  200 , the appliance  200  establishes, assigns or otherwise provides an IntranetIP address  282 , which is a network identifier, such as IP address and/or host name, for the client  102  on the second network  104 ′. The appliance  200  listens for and receives on the second or private network  104 ′ for any communications directed towards the client  102  using the client&#39;s established IntranetIP  282 . In one embodiment, the appliance  200  acts as or on behalf of the client  102  on the second private network  104 . For example, in another embodiment, a vServer  275  listens for and responds to communications to the IntranetIP  282  of the client  102 . In some embodiments, if a computing device  100  on the second network  104 ′ transmits a request, the appliance  200  processes the request as if it were the client  102 . For example, the appliance  200  may respond to a ping to the client&#39;s IntranetIP  282 . In another example, the appliance may establish a connection, such as a TCP or UDP connection, with computing device  100  on the second network  104  requesting a connection with the client&#39;s IntranetIP  282 . 
     In some embodiments, the appliance  200  provides one or more of the following acceleration techniques  288  to communications between the client  102  and server  106 : 1) compression; 2) decompression; 3) Transmission Control Protocol pooling; 4) Transmission Control Protocol multiplexing; 5) Transmission Control Protocol buffering; and 6) caching. In one embodiment, the appliance  200  relieves servers  106  of much of the processing load caused by repeatedly opening and closing transport layers connections to clients  102  by opening one or more transport layer connections with each server  106  and maintaining these connections to allow repeated data accesses by clients via the Internet. This technique is referred to herein as “connection pooling”. 
     In some embodiments, in order to seamlessly splice communications from a client  102  to a server  106  via a pooled transport layer connection, the appliance  200  translates or multiplexes communications by modifying sequence number and acknowledgment numbers at the transport layer protocol level. This is referred to as “connection multiplexing”. In some embodiments, no application layer protocol interaction is required. For example, in the case of an in-bound packet (that is, a packet received from a client  102 ), the source network address of the packet is changed to that of an output port of appliance  200 , and the destination network address is changed to that of the intended server. In the case of an outbound packet (that is, one received from a server  106 ), the source network address is changed from that of the server  106  to that of an output port of appliance  200  and the destination address is changed from that of appliance  200  to that of the requesting client  102 . The sequence numbers and acknowledgment numbers of the packet are also translated to sequence numbers and acknowledgement numbers expected by the client  102  on the appliance&#39;s  200  transport layer connection to the client  102 . In some embodiments, the packet checksum of the transport layer protocol is recalculated to account for these translations. 
     In another embodiment, the appliance  200  provides switching or load-balancing functionality  284  for communications between the client  102  and server  106 . In some embodiments, the appliance  200  distributes traffic and directs client requests to a server  106  based on layer 4 or application-layer request data. In one embodiment, although the network layer or layer 2 of the network packet identifies a destination server  106 , the appliance  200  determines the server  106  to distribute the network packet by application information and data carried as payload of the transport layer packet. In one embodiment, the health monitoring programs  216  of the appliance  200  monitor the health of servers to determine the server  106  for which to distribute a client&#39;s request. In some embodiments, if the appliance  200  detects a server  106  is not available or has a load over a predetermined threshold, the appliance  200  can direct or distribute client requests to another server  106 . 
     In some embodiments, the appliance  200  acts as a Domain Name Service (DNS) resolver or otherwise provides resolution of a DNS request from clients  102 . In some embodiments, the appliance intercepts a DNS request transmitted by the client  102 . In one embodiment, the appliance  200  responds to a client&#39;s DNS request with an IP address of or hosted by the appliance  200 . In this embodiment, the client  102  transmits network communication for the domain name to the appliance  200 . In another embodiment, the appliance  200  responds to a client&#39;s DNS request with an IP address of or hosted by a second appliance  200 ′. In some embodiments, the appliance  200  responds to a client&#39;s DNS request with an IP address of a server  106  determined by the appliance  200 . 
     In yet another embodiment, the appliance  200  provides application firewall functionality  290  for communications between the client  102  and server  106 . In one embodiment, the policy engine  236  provides rules for detecting and blocking illegitimate requests. In some embodiments, the application firewall  290  protects against denial of service (DoS) attacks. In other embodiments, the appliance inspects the content of intercepted requests to identify and block application-based attacks. In some embodiments, the rules/policy engine  236  comprises one or more application firewall or security control policies for providing protections against various classes and types of web or Internet based vulnerabilities, such as one or more of the following: 1) buffer overflow, 2) CGI-BIN parameter manipulation, 3) form/hidden field manipulation, 4) forceful browsing, 5) cookie or session poisoning, 6) broken access control list (ACLs) or weak passwords, 7) cross-site scripting (XSS), 8) command injection, 9) SQL injection, 10) error triggering sensitive information leak, 11) insecure use of cryptography, 12) server misconfiguration, 13) back doors and debug options, 14) website defacement, 15) platform or operating systems vulnerabilities, and 16) zero-day exploits. In an embodiment, the application firewall  290  provides HTML form field protection in the form of inspecting or analyzing the network communication for one or more of the following: 1) required fields are returned, 2) no added field allowed, 3) read-only and hidden field enforcement, 4) drop-down list and radio button field conformance, and 5) form-field max-length enforcement. In some embodiments, the application firewall  290  ensures cookies are not modified. In other embodiments, the application firewall  290  protects against forceful browsing by enforcing legal URLs. 
     In still yet other embodiments, the application firewall  290  protects any confidential information contained in the network communication. The application firewall  290  may inspect or analyze any network communication in accordance with the rules or polices of the engine  236  to identify any confidential information in any field of the network packet. In some embodiments, the application firewall  290  identifies in the network communication one or more occurrences of a credit card number, password, social security number, name, patient code, contact information, and age. The encoded portion of the network communication may comprise these occurrences or the confidential information. Based on these occurrences, in one embodiment, the application firewall  290  may take a policy action on the network communication, such as prevent transmission of the network communication. In another embodiment, the application firewall  290  may rewrite, remove or otherwise mask such identified occurrence or confidential information. 
     Still referring to  FIG. 2B , the appliance  200  may include a performance monitoring agent  197  as discussed above in conjunction with  FIG. 1D . In one embodiment, the appliance  200  receives the monitoring agent  197  from the monitoring service  198  or monitoring server  106  as depicted in  FIG. 1D . In some embodiments, the appliance  200  stores the monitoring agent  197  in storage, such as disk, for delivery to any client or server in communication with the appliance  200 . For example, in one embodiment, the appliance  200  transmits the monitoring agent  197  to a client upon receiving a request to establish a transport layer connection. In other embodiments, the appliance  200  transmits the monitoring agent  197  upon establishing the transport layer connection with the client  102 . In another embodiment, the appliance  200  transmits the monitoring agent  197  to the client upon intercepting or detecting a request for a web page. In yet another embodiment, the appliance  200  transmits the monitoring agent  197  to a client or a server in response to a request from the monitoring server  198 . In one embodiment, the appliance  200  transmits the monitoring agent  197  to a second appliance  200 ′ or appliance  205 . 
     In other embodiments, the appliance  200  executes the monitoring agent  197 . In one embodiment, the monitoring agent  197  measures and monitors the performance of any application, program, process, service, task or thread executing on the appliance  200 . For example, the monitoring agent  197  may monitor and measure performance and operation of vServers  275 A- 275 N. In another embodiment, the monitoring agent  197  measures and monitors the performance of any transport layer connections of the appliance  200 . In some embodiments, the monitoring agent  197  measures and monitors the performance of any user sessions traversing the appliance  200 . In one embodiment, the monitoring agent  197  measures and monitors the performance of any virtual private network connections and/or sessions traversing the appliance  200 , such an SSL VPN session. In still further embodiments, the monitoring agent  197  measures and monitors the memory, CPU and disk usage and performance of the appliance  200 . In yet another embodiment, the monitoring agent  197  measures and monitors the performance of any acceleration technique  288  performed by the appliance  200 , such as SSL offloading, connection pooling and multiplexing, caching, and compression. In some embodiments, the monitoring agent  197  measures and monitors the performance of any load balancing and/or content switching  284  performed by the appliance  200 . In other embodiments, the monitoring agent  197  measures and monitors the performance of application firewall  290  protection and processing performed by the appliance  200 . 
     C. Client Agent 
     Referring now to  FIG. 3 , an embodiment of the client agent  120  is depicted. The client  102  includes a client agent  120  for establishing and exchanging communications with the appliance  200  and/or server  106  via a network  104 . In brief overview, the client  102  operates on computing device  100  having an operating system with a kernel mode  302  and a user mode  303 , and a network stack  310  with one or more layers  310   a - 310   b . The client  102  may have installed and/or execute one or more applications. In some embodiments, one or more applications may communicate via the network stack  310  to a network  104 . One of the applications, such as a web browser, may also include a first program  322 . For example, the first program  322  may be used in some embodiments to install and/or execute the client agent  120 , or any portion thereof. The client agent  120  includes an interception mechanism, or interceptor  350 , for intercepting network communications from the network stack  310  from the one or more applications. 
     The network stack  310  of the client  102  may comprise any type and form of software, or hardware, or any combinations thereof, for providing connectivity to and communications with a network. In one embodiment, the network stack  310  comprises a software implementation for a network protocol suite. The network stack  310  may comprise one or more network layers, such as any networks layers of the Open Systems Interconnection (OSI) communications model as those skilled in the art recognize and appreciate. As such, the network stack  310  may comprise any type and form of protocols for any of the following layers of the OSI model: 1) physical link layer, 2) data link layer, 3) network layer, 4) transport layer, 5) session layer, 6) presentation layer, and 7) application layer. In one embodiment, the network stack  310  may comprise a transport control protocol (TCP) over the network layer protocol of the internet protocol (IP), generally referred to as TCP/IP. In some embodiments, the TCP/IP protocol may be carried over the Ethernet protocol, which may comprise any of the family of IEEE wide-area-network (WAN) or local-area-network (LAN) protocols, such as those protocols covered by the IEEE 802.3. In some embodiments, the network stack  310  comprises any type and form of a wireless protocol, such as IEEE 802.11 and/or mobile internet protocol. 
     In view of a TCP/IP based network, any TCP/IP based protocol may be used, including Messaging Application Programming Interface (MAPI) (email), File Transfer Protocol (FTP), HyperText Transfer Protocol (HTTP), Common Internet File System (CIFS) protocol (file transfer), Independent Computing Architecture (ICA) protocol, Remote Desktop Protocol (RDP), Wireless Application Protocol (WAP), Mobile IP protocol, and Voice Over IP (VoIP) protocol. In another embodiment, the network stack  310  comprises any type and form of transport control protocol, such as a modified transport control protocol, for example a Transaction TCP (T/TCP), TCP with selection acknowledgements (TCP-SACK), TCP with large windows (TCP-LW), a congestion prediction protocol such as the TCP-Vegas protocol, and a TCP spoofing protocol. In other embodiments, any type and form of user datagram protocol (UDP), such as UDP over IP, may be used by the network stack  310 , such as for voice communications or real-time data communications. 
     Furthermore, the network stack  310  may include one or more network drivers supporting the one or more layers, such as a TCP driver or a network layer driver. The network drivers may be included as part of the operating system of the computing device  100  or as part of any network interface cards or other network access components of the computing device  100 . In some embodiments, any of the network drivers of the network stack  310  may be customized, modified or adapted to provide a custom or modified portion of the network stack  310  in support of any of the techniques described herein. In other embodiments, the acceleration program  302  is designed and constructed to operate with or work in conjunction with the network stack  310  installed or otherwise provided by the operating system of the client  102 . 
     The network stack  310  comprises any type and form of interfaces for receiving, obtaining, providing or otherwise accessing any information and data related to network communications of the client  102 . In one embodiment, an interface to the network stack  310  comprises an application programming interface (API). The interface may also comprise any function call, hooking or filtering mechanism, event or call back mechanism, or any type of interfacing technique. The network stack  310  via the interface may receive or provide any type and form of data structure, such as an object, related to functionality or operation of the network stack  310 . For example, the data structure may comprise information and data related to a network packet or one or more network packets. In some embodiments, the data structure comprises a portion of the network packet processed at a protocol layer of the network stack  310 , such as a network packet of the transport layer. In some embodiments, the data structure  325  comprises a kernel-level data structure, while in other embodiments, the data structure  325  comprises a user-mode data structure. A kernel-level data structure may comprise a data structure obtained or related to a portion of the network stack  310  operating in kernel-mode  302 , or a network driver or other software running in kernel-mode  302 , or any data structure obtained or received by a service, process, task, thread or other executable instructions running or operating in kernel-mode of the operating system. 
     Additionally, some portions of the network stack  310  may execute or operate in kernel-mode  302 , for example, the data link or network layer, while other portions execute or operate in user-mode  303 , such as an application layer of the network stack  310 . For example, a first portion  310   a  of the network stack may provide user-mode access to the network stack  310  to an application while a second portion  310   a  of the network stack  310  provides access to a network. In some embodiments, a first portion  310   a  of the network stack may comprise one or more upper layers of the network stack  310 , such as any of layers 5-7. In other embodiments, a second portion  310   b  of the network stack  310  comprises one or more lower layers, such as any of layers 1-4. Each of the first portion  310   a  and second portion  310   b  of the network stack  310  may comprise any portion of the network stack  310 , at any one or more network layers, in user-mode  203 , kernel-mode,  202 , or combinations thereof, or at any portion of a network layer or interface point to a network layer or any portion of or interface point to the user-mode  203  and kernel-mode  203 . 
     The interceptor  350  may comprise software, hardware, or any combination of software and hardware. In one embodiment, the interceptor  350  intercept a network communication at any point in the network stack  310 , and redirects or transmits the network communication to a destination desired, managed or controlled by the interceptor  350  or client agent  120 . For example, the interceptor  350  may intercept a network communication of a network stack  310  of a first network and transmit the network communication to the appliance  200  for transmission on a second network  104 . In some embodiments, the interceptor  350  comprises any type interceptor  350  comprises a driver, such as a network driver constructed and designed to interface and work with the network stack  310 . In some embodiments, the client agent  120  and/or interceptor  350  operates at one or more layers of the network stack  310 , such as at the transport layer. In one embodiment, the interceptor  350  comprises a filter driver, hooking mechanism, or any form and type of suitable network driver interface that interfaces to the transport layer of the network stack, such as via the transport driver interface (TDI). In some embodiments, the interceptor  350  interfaces to a first protocol layer, such as the transport layer and another protocol layer, such as any layer above the transport protocol layer, for example, an application protocol layer. In one embodiment, the interceptor  350  may comprise a driver complying with the Network Driver Interface Specification (NDIS), or a NDIS driver. In another embodiment, the interceptor  350  may comprise a mini-filter or a mini-port driver. In one embodiment, the interceptor  350 , or portion thereof, operates in kernel-mode  202 . In another embodiment, the interceptor  350 , or portion thereof, operates in user-mode  203 . In some embodiments, a portion of the interceptor  350  operates in kernel-mode  202  while another portion of the interceptor  350  operates in user-mode  203 . In other embodiments, the client agent  120  operates in user-mode  203  but interfaces via the interceptor  350  to a kernel-mode driver, process, service, task or portion of the operating system, such as to obtain a kernel-level data structure  225 . In further embodiments, the interceptor  350  is a user-mode application or program, such as application. 
     In one embodiment, the interceptor  350  intercepts any transport layer connection requests. In these embodiments, the interceptor  350  execute transport layer application programming interface (API) calls to set the destination information, such as destination IP address and/or port to a desired location for the location. In this manner, the interceptor  350  intercepts and redirects the transport layer connection to a IP address and port controlled or managed by the interceptor  350  or client agent  120 . In one embodiment, the interceptor  350  sets the destination information for the connection to a local IP address and port of the client  102  on which the client agent  120  is listening. For example, the client agent  120  may comprise a proxy service listening on a local IP address and port for redirected transport layer communications. In some embodiments, the client agent  120  then communicates the redirected transport layer communication to the appliance  200 . 
     In some embodiments, the interceptor  350  intercepts a Domain Name Service (DNS) request. In one embodiment, the client agent  120  and/or interceptor  350  resolves the DNS request. In another embodiment, the interceptor transmits the intercepted DNS request to the appliance  200  for DNS resolution. In one embodiment, the appliance  200  resolves the DNS request and communicates the DNS response to the client agent  120 . In some embodiments, the appliance  200  resolves the DNS request via another appliance  200 ′ or a DNS server  106 . 
     In yet another embodiment, the client agent  120  may comprise two agents  120  and  120 ′. In one embodiment, a first agent  120  may comprise an interceptor  350  operating at the network layer of the network stack  310 . In some embodiments, the first agent  120  intercepts network layer requests such as Internet Control Message Protocol (ICMP) requests (e.g., ping and traceroute). In other embodiments, the second agent  120 ′ may operate at the transport layer and intercept transport layer communications. In some embodiments, the first agent  120  intercepts communications at one layer of the network stack  210  and interfaces with or communicates the intercepted communication to the second agent  120 ′. 
     The client agent  120  and/or interceptor  350  may operate at or interface with a protocol layer in a manner transparent to any other protocol layer of the network stack  310 . For example, in one embodiment, the interceptor  350  operates or interfaces with the transport layer of the network stack  310  transparently to any protocol layer below the transport layer, such as the network layer, and any protocol layer above the transport layer, such as the session, presentation or application layer protocols. This allows the other protocol layers of the network stack  310  to operate as desired and without modification for using the interceptor  350 . As such, the client agent  120  and/or interceptor  350  can interface with the transport layer to secure, optimize, accelerate, route or load-balance any communications provided via any protocol carried by the transport layer, such as any application layer protocol over TCP/IP. 
     Furthermore, the client agent  120  and/or interceptor may operate at or interface with the network stack  310  in a manner transparent to any application, a user of the client  102 , and any other computing device, such as a server, in communications with the client  102 . The client agent  120  and/or interceptor  350  may be installed and/or executed on the client  102  in a manner without modification of an application. In some embodiments, the user of the client  102  or a computing device in communications with the client  102  are not aware of the existence, execution or operation of the client agent  120  and/or interceptor  350 . As such, in some embodiments, the client agent  120  and/or interceptor  350  is installed, executed, and/or operated transparently to an application, user of the client  102 , another computing device, such as a server, or any of the protocol layers above and/or below the protocol layer interfaced to by the interceptor  350 . 
     The client agent  120  includes an acceleration program  302 , a streaming client  306 , a collection agent  304 , and/or monitoring agent  197 . In one embodiment, the client agent  120  comprises an Independent Computing Architecture (ICA) client, or any portion thereof, developed by Citrix Systems, Inc. of Fort Lauderdale, Fla., and is also referred to as an ICA client. In some embodiments, the client  120  comprises an application streaming client  306  for streaming an application from a server  106  to a client  102 . In some embodiments, the client agent  120  comprises an acceleration program  302  for accelerating communications between client  102  and server  106 . In another embodiment, the client agent  120  includes a collection agent  304  for performing end-point detection/scanning and collecting end-point information for the appliance  200  and/or server  106 . 
     In some embodiments, the acceleration program  302  comprises a client-side acceleration program for performing one or more acceleration techniques to accelerate, enhance or otherwise improve a client&#39;s communications with and/or access to a server  106 , such as accessing an application provided by a server  106 . The logic, functions, and/or operations of the executable instructions of the acceleration program  302  may perform one or more of the following acceleration techniques: 1) multi-protocol compression, 2) transport control protocol pooling, 3) transport control protocol multiplexing, 4) transport control protocol buffering, and 5) caching via a cache manager. Additionally, the acceleration program  302  may perform encryption and/or decryption of any communications received and/or transmitted by the client  102 . In some embodiments, the acceleration program  302  performs one or more of the acceleration techniques in an integrated manner or fashion. Additionally, the acceleration program  302  can perform compression on any of the protocols, or multiple-protocols, carried as a payload of a network packet of the transport layer protocol. 
     The streaming client  306  comprises an application, program, process, service, task or executable instructions for receiving and executing a streamed application from a server  106 . A server  106  may stream one or more application data files to the streaming client  306  for playing, executing or otherwise causing to be executed the application on the client  102 . In some embodiments, the server  106  transmits a set of compressed or packaged application data files to the streaming client  306 . In some embodiments, the plurality of application files are compressed and stored on a file server within an archive file such as a CAB, ZIP, SIT, TAR, JAR or other archive. In one embodiment, the server  106  decompresses, unpackages or unarchives the application files and transmits the files to the client  102 . In another embodiment, the client  102  decompresses, unpackages or unarchives the application files. The streaming client  306  dynamically installs the application, or portion thereof, and executes the application. In one embodiment, the streaming client  306  may be an executable program. In some embodiments, the streaming client  306  may be able to launch another executable program. 
     The collection agent  304  comprises an application, program, process, service, task or executable instructions for identifying, obtaining and/or collecting information about the client  102 . In some embodiments, the appliance  200  transmits the collection agent  304  to the client  102  or client agent  120 . The collection agent  304  may be configured according to one or more policies of the policy engine  236  of the appliance. In other embodiments, the collection agent  304  transmits collected information on the client  102  to the appliance  200 . In one embodiment, the policy engine  236  of the appliance  200  uses the collected information to determine and provide access, authentication and authorization control of the client&#39;s connection to a network  104 . 
     In one embodiment, the collection agent  304  comprises an end-point detection and scanning mechanism, which identifies and determines one or more attributes or characteristics of the client. For example, the collection agent  304  may identify and determine any one or more of the following client-side attributes: 1) the operating system an/or a version of an operating system, 2) a service pack of the operating system, 3) a running service, 4) a running process, and 5) a file. The collection agent  304  may also identify and determine the presence or versions of any one or more of the following on the client: 1) antivirus software, 2) personal firewall software, 3) anti-spam software, and 4) internet security software. The policy engine  236  may have one or more policies based on any one or more of the attributes or characteristics of the client or client-side attributes. 
     In some embodiments, the client agent  120  includes a monitoring agent  197  as discussed in conjunction with  FIGS. 1D and 2B . The monitoring agent  197  may be any type and form of script, such as Visual Basic or Java script. In one embodiment, the monitoring agent  197  monitors and measures performance of any portion of the client agent  120 . For example, in some embodiments, the monitoring agent  197  monitors and measures performance of the acceleration program  302 . In another embodiment, the monitoring agent  197  monitors and measures performance of the streaming client  306 . In other embodiments, the monitoring agent  197  monitors and measures performance of the collection agent  304 . In still another embodiment, the monitoring agent  197  monitors and measures performance of the interceptor  350 . In some embodiments, the monitoring agent  197  monitors and measures any resource of the client  102 , such as memory, CPU and disk. 
     The monitoring agent  197  may monitor and measure performance of any application of the client. In one embodiment, the monitoring agent  197  monitors and measures performance of a browser on the client  102 . In some embodiments, the monitoring agent  197  monitors and measures performance of any application delivered via the client agent  120 . In other embodiments, the monitoring agent  197  measures and monitors end user response times for an application, such as web-based or HTTP response times. The monitoring agent  197  may monitor and measure performance of an ICA or RDP client. In another embodiment, the monitoring agent  197  measures and monitors metrics for a user session or application session. In some embodiments, monitoring agent  197  measures and monitors an ICA or RDP session. In one embodiment, the monitoring agent  197  measures and monitors the performance of the appliance  200  in accelerating delivery of an application and/or data to the client  102 . 
     In some embodiments and still referring to  FIG. 3 , a first program  322  may be used to install and/or execute the client agent  120 , or portion thereof, such as the interceptor  350 , automatically, silently, transparently, or otherwise. In one embodiment, the first program  322  comprises a plugin component, such an ActiveX control or Java control or script that is loaded into and executed by an application. For example, the first program comprises an ActiveX control loaded and run by a web browser application, such as in the memory space or context of the application. In another embodiment, the first program  322  comprises a set of executable instructions loaded into and run by the application, such as a browser. In one embodiment, the first program  322  comprises a designed and constructed program to install the client agent  120 . In some embodiments, the first program  322  obtains, downloads, or receives the client agent  120  via the network from another computing device. In another embodiment, the first program  322  is an installer program or a plug and play manager for installing programs, such as network drivers, on the operating system of the client  102 . 
     D. Systems and Methods for Providing Virtualized Application Delivery Controller 
     Referring now to  FIG. 4A , a block diagram depicts one embodiment of a virtualization environment  400 . In brief overview, a computing device  100  includes a hypervisor layer, a virtualization layer, and a hardware layer. The hypervisor layer includes a hypervisor  401  (also referred to as a virtualization manager) that allocates and manages access to a number of physical resources in the hardware layer (e.g., the processor(s)  421 , and disk(s)  428 ) by at least one virtual machine executing in the virtualization layer. The virtualization layer includes at least one operating system  410  and a plurality of virtual resources allocated to the at least one operating system  410 . Virtual resources may include, without limitation, a plurality of virtual processors  432   a ,  432   b ,  432   c  (generally  432 ), and virtual disks  442   a ,  442   b ,  442   c  (generally  442 ), as well as virtual resources such as virtual memory and virtual network interfaces. The plurality of virtual resources and the operating system  410  may be referred to as a virtual machine  406 . A virtual machine  406  may include a control operating system  405  in communication with the hypervisor  401  and used to execute applications for managing and configuring other virtual machines on the computing device  100 . 
     In greater detail, a hypervisor  401  may provide virtual resources to an operating system in any manner which simulates the operating system having access to a physical device. A hypervisor  401  may provide virtual resources to any number of guest operating systems  410   a ,  410   b  (generally  410 ). In some embodiments, a computing device  100  executes one or more types of hypervisors. In these embodiments, hypervisors may be used to emulate virtual hardware, partition physical hardware, virtualize physical hardware, and execute virtual machines that provide access to computing environments. Hypervisors may include those manufactured by VMWare, Inc., of Palo Alto, Calif.; the XEN hypervisor, an open source product whose development is overseen by the open source Xen.org community; HyperV, VirtualServer or virtual PC hypervisors provided by Microsoft, or others. In some embodiments, a computing device  100  executing a hypervisor that creates a virtual machine platform on which guest operating systems may execute is referred to as a host server. In one of these embodiments, for example, the computing device  100  is a XEN SERVER provided by Citrix Systems, Inc., of Fort Lauderdale, Fla. 
     In some embodiments, a hypervisor  401  executes within an operating system executing on a computing device. In one of these embodiments, a computing device executing an operating system and a hypervisor  401  may be said to have a host operating system (the operating system executing on the computing device), and a guest operating system (an operating system executing within a computing resource partition provided by the hypervisor  401 ). In other embodiments, a hypervisor  401  interacts directly with hardware on a computing device, instead of executing on a host operating system. In one of these embodiments, the hypervisor  401  may be said to be executing on “bare metal,” referring to the hardware comprising the computing device. 
     In some embodiments, a hypervisor  401  may create a virtual machine  406   a - c  (generally  406 ) in which an operating system  410  executes. In one of these embodiments, for example, the hypervisor  401  loads a virtual machine image to create a virtual machine  406 . In another of these embodiments, the hypervisor  401  executes an operating system  410  within the virtual machine  406 . In still another of these embodiments, the virtual machine  406  executes an operating system  410 . 
     In some embodiments, the hypervisor  401  controls processor scheduling and memory partitioning for a virtual machine  406  executing on the computing device  100 . In one of these embodiments, the hypervisor  401  controls the execution of at least one virtual machine  406 . In another of these embodiments, the hypervisor  401  presents at least one virtual machine  406  with an abstraction of at least one hardware resource provided by the computing device  100 . In other embodiments, the hypervisor  401  controls whether and how physical processor capabilities are presented to the virtual machine  406 . 
     A control operating system  405  may execute at least one application for managing and configuring the guest operating systems. In one embodiment, the control operating system  405  may execute an administrative application, such as an application including a user interface providing administrators with access to functionality for managing the execution of a virtual machine, including functionality for executing a virtual machine, terminating an execution of a virtual machine, or identifying a type of physical resource for allocation to the virtual machine. In another embodiment, the hypervisor  401  executes the control operating system  405  within a virtual machine  406  created by the hypervisor  401 . In still another embodiment, the control operating system  405  executes in a virtual machine  406  that is authorized to directly access physical resources on the computing device  100 . In some embodiments, a control operating system  405   a  on a computing device  100   a  may exchange data with a control operating system  405   b  on a computing device  100   b , via communications between a hypervisor  401   a  and a hypervisor  401   b . In this way, one or more computing devices  100  may exchange data with one or more of the other computing devices  100  regarding processors and other physical resources available in a pool of resources. In one of these embodiments, this functionality allows a hypervisor to manage a pool of resources distributed across a plurality of physical computing devices. In another of these embodiments, multiple hypervisors manage one or more of the guest operating systems executed on one of the computing devices  100 . 
     In one embodiment, the control operating system  405  executes in a virtual machine  406  that is authorized to interact with at least one guest operating system  410 . In another embodiment, a guest operating system  410  communicates with the control operating system  405  via the hypervisor  401  in order to request access to a disk or a network. In still another embodiment, the guest operating system  410  and the control operating system  405  may communicate via a communication channel established by the hypervisor  401 , such as, for example, via a plurality of shared memory pages made available by the hypervisor  401 . 
     In some embodiments, the control operating system  405  includes a network back-end driver for communicating directly with networking hardware provided by the computing device  100 . In one of these embodiments, the network back-end driver processes at least one virtual machine request from at least one guest operating system  110 . In other embodiments, the control operating system  405  includes a block back-end driver for communicating with a storage element on the computing device  100 . In one of these embodiments, the block back-end driver reads and writes data from the storage element based upon at least one request received from a guest operating system  410 . 
     In one embodiment, the control operating system  405  includes a tools stack  404 . In another embodiment, a tools stack  404  provides functionality for interacting with the hypervisor  401 , communicating with other control operating systems  405  (for example, on a second computing device  100   b ), or managing virtual machines  406   b ,  406   c  on the computing device  100 . In another embodiment, the tools stack  404  includes customized applications for providing improved management functionality to an administrator of a virtual machine farm. In some embodiments, at least one of the tools stack  404  and the control operating system  405  include a management API that provides an interface for remotely configuring and controlling virtual machines  406  running on a computing device  100 . In other embodiments, the control operating system  405  communicates with the hypervisor  401  through the tools stack  404 . 
     In one embodiment, the hypervisor  401  executes a guest operating system  410  within a virtual machine  406  created by the hypervisor  401 . In another embodiment, the guest operating system  410  provides a user of the computing device  100  with access to resources within a computing environment. In still another embodiment, a resource includes a program, an application, a document, a file, a plurality of applications, a plurality of files, an executable program file, a desktop environment, a computing environment, or other resource made available to a user of the computing device  100 . In yet another embodiment, the resource may be delivered to the computing device  100  via a plurality of access methods including, but not limited to, conventional installation directly on the computing device  100 , delivery to the computing device  100  via a method for application streaming, delivery to the computing device  100  of output data generated by an execution of the resource on a second computing device  100 ′ and communicated to the computing device  100  via a presentation layer protocol, delivery to the computing device  100  of output data generated by an execution of the resource via a virtual machine executing on a second computing device  100 ′, or execution from a removable storage device connected to the computing device  100 , such as a USB device, or via a virtual machine executing on the computing device  100  and generating output data. In some embodiments, the computing device  100  transmits output data generated by the execution of the resource to another computing device  100 ′. 
     In one embodiment, the guest operating system  410 , in conjunction with the virtual machine on which it executes, forms a fully-virtualized virtual machine which is not aware that it is a virtual machine; such a machine may be referred to as a “Domain U HVM (Hardware Virtual Machine) virtual machine”. In another embodiment, a fully-virtualized machine includes software emulating a Basic Input/Output System (BIOS) in order to execute an operating system within the fully-virtualized machine. In still another embodiment, a fully-virtualized machine may include a driver that provides functionality by communicating with the hypervisor  401 . In such an embodiment, the driver may be aware that it executes within a virtualized environment. In another embodiment, the guest operating system  410 , in conjunction with the virtual machine on which it executes, forms a paravirtualized virtual machine, which is aware that it is a virtual machine; such a machine may be referred to as a “Domain U PV virtual machine”. In another embodiment, a paravirtualized machine includes additional drivers that a fully-virtualized machine does not include. In still another embodiment, the paravirtualized machine includes the network back-end driver and the block back-end driver included in a control operating system  405 , as described above. 
     Referring now to  FIG. 4B , a block diagram depicts one embodiment of a plurality of networked computing devices in a system in which at least one physical host executes a virtual machine. In brief overview, the system includes a management component  404  and a hypervisor  401 . The system includes a plurality of computing devices  100 , a plurality of virtual machines  406 , a plurality of hypervisors  401 , a plurality of management components referred to variously as tools stacks  404  or management components  404 , and a physical resource  421 ,  428 . The plurality of physical machines  100  may each be provided as computing devices  100 , described above in connection with  FIGS. 1E-1H and 4A . 
     In greater detail, a physical disk  428  is provided by a computing device  100  and stores at least a portion of a virtual disk  442 . In some embodiments, a virtual disk  442  is associated with a plurality of physical disks  428 . In one of these embodiments, one or more computing devices  100  may exchange data with one or more of the other computing devices  100  regarding processors and other physical resources available in a pool of resources, allowing a hypervisor to manage a pool of resources distributed across a plurality of physical computing devices. In some embodiments, a computing device  100  on which a virtual machine  406  executes is referred to as a physical host  100  or as a host machine  100 . 
     The hypervisor executes on a processor on the computing device  100 . The hypervisor allocates, to a virtual disk, an amount of access to the physical disk. In one embodiment, the hypervisor  401  allocates an amount of space on the physical disk. In another embodiment, the hypervisor  401  allocates a plurality of pages on the physical disk. In some embodiments, the hypervisor provisions the virtual disk  442  as part of a process of initializing and executing a virtual machine  450 . 
     In one embodiment, the management component  404   a  is referred to as a pool management component  404   a . In another embodiment, a management operating system  405   a , which may be referred to as a control operating system  405   a , includes the management component. In some embodiments, the management component is referred to as a tools stack. In one of these embodiments, the management component is the tools stack  404  described above in connection with  FIG. 4A . In other embodiments, the management component  404  provides a user interface for receiving, from a user such as an administrator, an identification of a virtual machine  406  to provision and/or execute. In still other embodiments, the management component  404  provides a user interface for receiving, from a user such as an administrator, the request for migration of a virtual machine  406   b  from one physical machine  100  to another. In further embodiments, the management component  404   a  identifies a computing device  100   b  on which to execute a requested virtual machine  406   d  and instructs the hypervisor  401   b  on the identified computing device  100   b  to execute the identified virtual machine; such a management component may be referred to as a pool management component. 
     Referring now to  FIG. 4C , embodiments of a virtual application delivery controller or virtual appliance  450  are depicted. In brief overview, any of the functionality and/or embodiments of the appliance  200  (e.g., an application delivery controller) described above in connection with  FIGS. 2A and 2B  may be deployed in any embodiment of the virtualized environment described above in connection with  FIGS. 4A and 4B . Instead of the functionality of the application delivery controller being deployed in the form of an appliance  200 , such functionality may be deployed in a virtualized environment  400  on any computing device  100 , such as a client  102 , server  106  or appliance  200 . 
     Referring now to  FIG. 4C , a diagram of an embodiment of a virtual appliance  450  operating on a hypervisor  401  of a server  106  is depicted. As with the appliance  200  of  FIGS. 2A and 2B , the virtual appliance  450  may provide functionality for availability, performance, offload and security. For availability, the virtual appliance may perform load balancing between layers 4 and 7 of the network and may also perform intelligent service health monitoring. For performance increases via network traffic acceleration, the virtual appliance may perform caching and compression. To offload processing of any servers, the virtual appliance may perform connection multiplexing and pooling and/or SSL processing. For security, the virtual appliance may perform any of the application firewall functionality and SSL VPN function of appliance  200 . 
     Any of the modules of the appliance  200  as described in connection with  FIG. 2A  may be packaged, combined, designed or constructed in a form of the virtualized appliance delivery controller  450  deployable as one or more software modules or components executable in a virtualized environment  300  or non-virtualized environment on any server, such as an off the shelf server. For example, the virtual appliance may be provided in the form of an installation package to install on a computing device. With reference to  FIG. 2A , any of the cache manager  232 , policy engine  236 , compression  238 , encryption engine  234 , packet engine  240 , GUI  210 , CLI  212 , shell services  214  and health monitoring programs  216  may be designed and constructed as a software component or module to run on any operating system of a computing device and/or of a virtualized environment  300 . Instead of using the encryption processor  260 , processor  262 , memory  264  and network stack  267  of the appliance  200 , the virtualized appliance  400  may use any of these resources as provided by the virtualized environment  400  or as otherwise available on the server  106 . 
     Still referring to  FIG. 4C , and in brief overview, any one or more vServers  275 A- 275 N may be in operation or executed in a virtualized environment  400  of any type of computing device  100 , such as any server  106 . Any of the modules or functionality of the appliance  200  described in connection with  FIG. 2B  may be designed and constructed to operate in either a virtualized or non-virtualized environment of a server. Any of the vServer  275 , SSL VPN  280 , Intranet UP  282 , Switching  284 , DNS  286 , acceleration  288 , App FW  280  and monitoring agent may be packaged, combined, designed or constructed in a form of application delivery controller  450  deployable as one or more software modules or components executable on a device and/or virtualized environment  400 . 
     In some embodiments, a server may execute multiple virtual machines  406   a - 406   n  in the virtualization environment with each virtual machine running the same or different embodiments of the virtual application delivery controller  450 . In some embodiments, the server may execute one or more virtual appliances  450  on one or more virtual machines on a core of a multi-core processing system. In some embodiments, the server may execute one or more virtual appliances  450  on one or more virtual machines on each processor of a multiple processor device. 
     E. Systems and Methods for Providing a Multi-Core Architecture 
     In accordance with Moore&#39;s Law, the number of transistors that may be placed on an integrated circuit may double approximately every two years. However, CPU speed increases may reach plateaus, for example CPU speed has been around 3.5-4 GHz range since 2005. In some cases, CPU manufacturers may not rely on CPU speed increases to gain additional performance. Some CPU manufacturers may add additional cores to their processors to provide additional performance. Products, such as those of software and networking vendors, that rely on CPUs for performance gains may improve their performance by leveraging these multi-core CPUs. The software designed and constructed for a single CPU may be redesigned and/or rewritten to take advantage of a multi-threaded, parallel architecture or otherwise a multi-core architecture. 
     A multi-core architecture of the appliance  200 , referred to as nCore or multi-core technology, allows the appliance in some embodiments to break the single core performance barrier and to leverage the power of multi-core CPUs. In the previous architecture described in connection with  FIG. 2A , a single network or packet engine is run. The multiple cores of the nCore technology and architecture allow multiple packet engines to run concurrently and/or in parallel. With a packet engine running on each core, the appliance architecture leverages the processing capacity of additional cores. In some embodiments, this provides up to a 7× increase in performance and scalability. 
     Illustrated in  FIG. 5A  are some embodiments of work, task, load or network traffic distribution across one or more processor cores according to a type of parallelism or parallel computing scheme, such as functional parallelism, data parallelism or flow-based data parallelism. In brief overview,  FIG. 5A  illustrates embodiments of a multi-core system such as an appliance  200 ′ with n-cores, a total of cores numbers 1 through N. In one embodiment, work, load or network traffic can be distributed among a first core  505 A, a second core  505 B, a third core  505 C, a fourth core  505 D, a fifth core  505 E, a sixth core  505 F, a seventh core  505 G, and so on such that distribution is across all or two or more of the n cores  505 N (hereinafter referred to collectively as cores  505 .) There may be multiple VIPs  275  each running on a respective core of the plurality of cores. There may be multiple packet engines  240  each running on a respective core of the plurality of cores. Any of the approaches used may lead to different, varying or similar work load or performance level  515  across any of the cores. For a functional parallelism approach, each core may run a different function of the functionalities provided by the packet engine, a VIP  275  or appliance  200 . In a data parallelism approach, data may be paralleled or distributed across the cores based on the Network Interface Card (NIC) or VIP  275  receiving the data. In another data parallelism approach, processing may be distributed across the cores by distributing data flows to each core. 
     In further detail to  FIG. 5A , in some embodiments, load, work or network traffic can be distributed among cores  505  according to functional parallelism  500 . Functional parallelism may be based on each core performing one or more respective functions. In some embodiments, a first core may perform a first function while a second core performs a second function. In functional parallelism approach, the functions to be performed by the multi-core system are divided and distributed to each core according to functionality. In some embodiments, functional parallelism may be referred to as task parallelism and may be achieved when each processor or core executes a different process or function on the same or different data. The core or processor may execute the same or different code. In some cases, different execution threads or code may communicate with one another as they work. Communication may take place to pass data from one thread to the next as part of a workflow. 
     In some embodiments, distributing work across the cores  505  according to functional parallelism  500 , can comprise distributing network traffic according to a particular function such as network input/output management (NW I/O)  510 A, secure sockets layer (SSL) encryption and decryption  510 B and transmission control protocol (TCP) functions  510 C. This may lead to a work, performance or computing load  515  based on a volume or level of functionality being used. In some embodiments, distributing work across the cores  505  according to data parallelism  540 , can comprise distributing an amount of work  515  based on distributing data associated with a particular hardware or software component. In some embodiments, distributing work across the cores  505  according to flow-based data parallelism  520 , can comprise distributing data based on a context or flow such that the amount of work  515 A-N on each core may be similar, substantially equal or relatively evenly distributed. 
     In the case of the functional parallelism approach, each core may be configured to run one or more functionalities of the plurality of functionalities provided by the packet engine or VIP of the appliance. For example, core  1  may perform network I/O processing for the appliance  200 ′ while core  2  performs TCP connection management for the appliance. Likewise, core  3  may perform SSL offloading while core  4  may perform layer 7 or application layer processing and traffic management. Each of the cores may perform the same function or different functions. Each of the cores may perform more than one function. Any of the cores may run any of the functionality or portions thereof identified and/or described in conjunction with  FIGS. 2A and 2B . In this the approach, the work across the cores may be divided by function in either a coarse-grained or fine-grained manner. In some cases, as illustrated in  FIG. 5A , division by function may lead to different cores running at different levels of performance or load  515 . 
     In the case of the functional parallelism approach, each core may be configured to run one or more functionalities of the plurality of functionalities provided by the packet engine of the appliance. For example, core  1  may perform network I/O processing for the appliance  200 ′ while core  2  performs TCP connection management for the appliance. Likewise, core  3  may perform SSL offloading while core  4  may perform layer 7 or application layer processing and traffic management. Each of the cores may perform the same function or different functions. Each of the cores may perform more than one function. Any of the cores may run any of the functionality or portions thereof identified and/or described in conjunction with  FIGS. 2A and 2B . In this the approach, the work across the cores may be divided by function in either a coarse-grained or fine-grained manner. In some cases, as illustrated in  FIG. 5A  division by function may lead to different cores running at different levels of load or performance. 
     The functionality or tasks may be distributed in any arrangement and scheme. For example,  FIG. 5B  illustrates a first core, Core  1   505 A, processing applications and processes associated with network I/O functionality  510 A. Network traffic associated with network I/O, in some embodiments, can be associated with a particular port number. Thus, outgoing and incoming packets having a port destination associated with NW I/O  510 A will be directed towards Core  1   505 A which is dedicated to handling all network traffic associated with the NW I/O port. Similarly, Core  2   505 B is dedicated to handling functionality associated with SSL processing and Core  4   505 D may be dedicated handling all TCP level processing and functionality. 
     While  FIG. 5A  illustrates functions such as network I/O, SSL and TCP, other functions can be assigned to cores. These other functions can include any one or more of the functions or operations described herein. For example, any of the functions described in conjunction with  FIGS. 2A and 2B  may be distributed across the cores on a functionality basis. In some cases, a first VIP  275 A may run on a first core while a second VIP  275 B with a different configuration may run on a second core. In some embodiments, each core  505  can handle a particular functionality such that each core  505  can handle the processing associated with that particular function. For example, Core  2   505 B may handle SSL offloading while Core  4   505 D may handle application layer processing and traffic management. 
     In other embodiments, work, load or network traffic may be distributed among cores  505  according to any type and form of data parallelism  540 . In some embodiments, data parallelism may be achieved in a multi-core system by each core performing the same task or functionally on different pieces of distributed data. In some embodiments, a single execution thread or code controls operations on all pieces of data. In other embodiments, different threads or instructions control the operation, but may execute the same code. In some embodiments, data parallelism is achieved from the perspective of a packet engine, vServers (VIPs)  275 A-C, network interface cards (NIC)  542 D-E and/or any other networking hardware or software included on or associated with an appliance  200 . For example, each core may run the same packet engine or VIP code or configuration but operate on different sets of distributed data. Each networking hardware or software construct can receive different, varying or substantially the same amount of data, and as a result may have varying, different or relatively the same amount of load  515 . 
     In the case of a data parallelism approach, the work may be divided up and distributed based on VIPs, NICs and/or data flows of the VIPs or NICs. In one of these approaches, the work of the multi-core system may be divided or distributed among the VIPs by having each VIP work on a distributed set of data. For example, each core may be configured to run one or more VIPs. Network traffic may be distributed to the core for each VIP handling that traffic. In another of these approaches, the work of the appliance may be divided or distributed among the cores based on which NIC receives the network traffic. For example, network traffic of a first NIC may be distributed to a first core while network traffic of a second NIC may be distributed to a second core. In some cases, a core may process data from multiple NICs. 
     While  FIG. 5A  illustrates a single vServer associated with a single core  505 , as is the case for VIP 1   275 A, VIP 2   275 B and VIP 3   275 C. In some embodiments, a single vServer can be associated with one or more cores  505 . In contrast, one or more vServers can be associated with a single core  505 . Associating a vServer with a core  505  may include that core  505  to process all functions associated with that particular vServer. In some embodiments, each core executes a VIP having the same code and configuration. In other embodiments, each core executes a VIP having the same code but different configuration. In some embodiments, each core executes a VIP having different code and the same or different configuration. 
     Like vServers, NICs can also be associated with particular cores  505 . In many embodiments, NICs can be connected to one or more cores  505  such that when a NIC receives or transmits data packets, a particular core  505  handles the processing involved with receiving and transmitting the data packets. In one embodiment, a single NIC can be associated with a single core  505 , as is the case with NIC 1   542 D and NIC 2   542 E. In other embodiments, one or more NICs can be associated with a single core  505 . In other embodiments, a single NIC can be associated with one or more cores  505 . In these embodiments, load could be distributed amongst the one or more cores  505  such that each core  505  processes a substantially similar amount of load. A core  505  associated with a NIC may process all functions and/or data associated with that particular NIC. 
     While distributing work across cores based on data of VIPs or NICs may have a level of independency, in some embodiments, this may lead to unbalanced use of cores as illustrated by the varying loads  515  of  FIG. 5A . 
     In some embodiments, load, work or network traffic can be distributed among cores  505  based on any type and form of data flow. In another of these approaches, the work may be divided or distributed among cores based on data flows. For example, network traffic between a client and a server traversing the appliance may be distributed to and processed by one core of the plurality of cores. In some cases, the core initially establishing the session or connection may be the core for which network traffic for that session or connection is distributed. In some embodiments, the data flow is based on any unit or portion of network traffic, such as a transaction, a request/response communication or traffic originating from an application on a client. In this manner and in some embodiments, data flows between clients and servers traversing the appliance  200 ′ may be distributed in a more balanced manner than the other approaches. 
     In flow-based data parallelism  520 , distribution of data is related to any type of flow of data, such as request/response pairings, transactions, sessions, connections or application communications. For example, network traffic between a client and a server traversing the appliance may be distributed to and processed by one core of the plurality of cores. In some cases, the core initially establishing the session or connection may be the core for which network traffic for that session or connection is distributed. The distribution of data flow may be such that each core  505  carries a substantially equal or relatively evenly distributed amount of load, data or network traffic. 
     In some embodiments, the data flow is based on any unit or portion of network traffic, such as a transaction, a request/response communication or traffic originating from an application on a client. In this manner and in some embodiments, data flows between clients and servers traversing the appliance  200 ′ may be distributed in a more balanced manner than the other approached. In one embodiment, data flow can be distributed based on a transaction or a series of transactions. This transaction, in some embodiments, can be between a client and a server and can be characterized by an IP address or other packet identifier. For example, Core  1   505 A can be dedicated to transactions between a particular client and a particular server, therefore the load  515 A on Core  1   505 A may be comprised of the network traffic associated with the transactions between the particular client and server. Allocating the network traffic to Core  1   505 A can be accomplished by routing all data packets originating from either the particular client or server to Core  1   505 A. 
     While work or load can be distributed to the cores based in part on transactions, in other embodiments load or work can be allocated on a per packet basis. In these embodiments, the appliance  200  can intercept data packets and allocate them to a core  505  having the least amount of load. For example, the appliance  200  could allocate a first incoming data packet to Core  1   505 A because the load  515 A on Core  1  is less than the load  515 B-N on the rest of the cores  505 B-N. Once the first data packet is allocated to Core  1   505 A, the amount of load  515 A on Core  1   505 A is increased proportional to the amount of processing resources needed to process the first data packet. When the appliance  200  intercepts a second data packet, the appliance  200  will allocate the load to Core  4   505 D because Core  4   505 D has the second least amount of load. Allocating data packets to the core with the least amount of load can, in some embodiments, ensure that the load  515 A-N distributed to each core  505  remains substantially equal. 
     In other embodiments, load can be allocated on a per unit basis where a section of network traffic is allocated to a particular core  505 . The above-mentioned example illustrates load balancing on a per/packet basis. In other embodiments, load can be allocated based on a number of packets such that every 10, 100 or 1000 packets are allocated to the core  505  having the least amount of load. The number of packets allocated to a core  505  can be a number determined by an application, user or administrator and can be any number greater than zero. In still other embodiments, load can be allocated based on a time metric such that packets are distributed to a particular core  505  for a predetermined amount of time. In these embodiments, packets can be distributed to a particular core  505  for five milliseconds or for any period of time determined by a user, program, system, administrator or otherwise. After the predetermined time period elapses, data packets are transmitted to a different core  505  for the predetermined period of time. 
     Flow-based data parallelism methods for distributing work, load or network traffic among the one or more cores  505  can comprise any combination of the above-mentioned embodiments. These methods can be carried out by any part of the appliance  200 , by an application or set of executable instructions executing on one of the cores  505 , such as the packet engine, or by any application, program or agent executing on a computing device in communication with the appliance  200 . 
     The functional and data parallelism computing schemes illustrated in  FIG. 5A  can be combined in any manner to generate a hybrid parallelism or distributed processing scheme that encompasses function parallelism  500 , data parallelism  540 , flow-based data parallelism  520  or any portions thereof. In some cases, the multi-core system may use any type and form of load balancing schemes to distribute load among the one or more cores  505 . The load balancing scheme may be used in any combination with any of the functional and data parallelism schemes or combinations thereof. 
     Illustrated in  FIG. 5B  is an embodiment of a multi-core system  545 , which may be any type and form of one or more systems, appliances, devices or components. This system  545 , in some embodiments, can be included within an appliance  200  having one or more processing cores  505 A-N. The system  545  can further include one or more packet engines (PE) or packet processing engines (PPE)  548 A-N communicating with a memory bus  556 . The memory bus may be used to communicate with the one or more processing cores  505 A-N. Also included within the system  545  can be one or more network interface cards (NIC)  552  and a flow distributor  550  which can further communicate with the one or more processing cores  505 A-N. The flow distributor  550  can comprise a Receive Side Scaler (RSS) or Receive Side Scaling (RSS) module  560 . 
     Further referring to  FIG. 5B , and in more detail, in one embodiment the packet engine(s)  548 A-N can comprise any portion of the appliance  200  described herein, such as any portion of the appliance described in  FIGS. 2A and 2B . The packet engine(s)  548 A-N can, in some embodiments, comprise any of the following elements: the packet engine  240 , a network stack  267 ; a cache manager  232 ; a policy engine  236 ; a compression engine  238 ; an encryption engine  234 ; a GUI  210 ; a CLI  212 ; shell services  214 ; monitoring programs  216 ; and any other software or hardware element able to receive data packets from one of either the memory bus  556  or the one of more cores  505 A-N. In some embodiments, the packet engine(s)  548 A-N can comprise one or more vServers  275 A-N, or any portion thereof. In other embodiments, the packet engine(s)  548 A-N can provide any combination of the following functionalities: SSL VPN  280 ; Intranet UP  282 ; switching  284 ; DNS  286 ; packet acceleration  288 ; App FW  280 ; monitoring such as the monitoring provided by a monitoring agent  197 ; functionalities associated with functioning as a TCP stack; load balancing; SSL offloading and processing; content switching; policy evaluation; caching; compression; encoding; decompression; decoding; application firewall functionalities; XML processing and acceleration; and SSL VPN connectivity. 
     The packet engine(s)  548 A-N can, in some embodiments, be associated with a particular server, user, client or network. When a packet engine  548  becomes associated with a particular entity, that packet engine  548  can process data packets associated with that entity. For example, should a packet engine  548  be associated with a first user, that packet engine  548  will process and operate on packets generated by the first user, or packets having a destination address associated with the first user. Similarly, the packet engine  548  may choose not to be associated with a particular entity such that the packet engine  548  can process and otherwise operate on any data packets not generated by that entity or destined for that entity. 
     In some instances, the packet engine(s)  548 A-N can be configured to carry out the any of the functional and/or data parallelism schemes illustrated in  FIG. 5A . In these instances, the packet engine(s)  548 A-N can distribute functions or data among the processing cores  505 A-N so that the distribution is according to the parallelism or distribution scheme. In some embodiments, a single packet engine(s)  548 A-N carries out a load balancing scheme, while in other embodiments one or more packet engine(s)  548 A-N carry out a load balancing scheme. Each core  505 A-N, in one embodiment, can be associated with a particular packet engine  548  such that load balancing can be carried out by the packet engine. Load balancing may in this embodiment, require that each packet engine  548 A-N associated with a core  505  communicate with the other packet engines associated with cores so that the packet engines  548 A-N can collectively determine where to distribute load. One embodiment of this process can include an arbiter that receives votes from each packet engine for load. The arbiter can distribute load to each packet engine  548 A-N based in part on the age of the engine&#39;s vote and in some cases a priority value associated with the current amount of load on an engine&#39;s associated core  505 . 
     Any of the packet engines running on the cores may run in user mode, kernel or any combination thereof. In some embodiments, the packet engine operates as an application or program running is user or application space. In these embodiments, the packet engine may use any type and form of interface to access any functionality provided by the kernel. In some embodiments, the packet engine operates in kernel mode or as part of the kernel. In some embodiments, a first portion of the packet engine operates in user mode while a second portion of the packet engine operates in kernel mode. In some embodiments, a first packet engine on a first core executes in kernel mode while a second packet engine on a second core executes in user mode. In some embodiments, the packet engine or any portions thereof operates on or in conjunction with the NIC or any drivers thereof. 
     In some embodiments the memory bus  556  can be any type and form of memory or computer bus. While a single memory bus  556  is depicted in  FIG. 5B , the system  545  can comprise any number of memory buses  556 . In one embodiment, each packet engine  548  can be associated with one or more individual memory buses  556 . 
     The NIC  552  can in some embodiments be any of the network interface cards or mechanisms described herein. The NIC  552  can have any number of ports. The NIC can be designed and constructed to connect to any type and form of network  104 . While a single NIC  552  is illustrated, the system  545  can comprise any number of NICs  552 . In some embodiments, each core  505 A-N can be associated with one or more single NICs  552 . Thus, each core  505  can be associated with a single NIC  552  dedicated to a particular core  505 . The cores  505 A-N can comprise any of the processors described herein. Further, the cores  505 A-N can be configured according to any of the core  505  configurations described herein. Still further, the cores  505 A-N can have any of the core  505  functionalities described herein. While  FIG. 5B  illustrates seven cores  505 A-G, any number of cores  505  can be included within the system  545 . In particular, the system  545  can comprise “N” cores, where “N” is a whole number greater than zero. 
     A core may have or use memory that is allocated or assigned for use to that core. The memory may be considered private or local memory of that core and only accessible by that core. A core may have or use memory that is shared or assigned to multiple cores. The memory may be considered public or shared memory that is accessible by more than one core. A core may use any combination of private and public memory. With separate address spaces for each core, some level of coordination is eliminated from the case of using the same address space. With a separate address space, a core can perform work on information and data in the core&#39;s own address space without worrying about conflicts with other cores. Each packet engine may have a separate memory pool for TCP and/or SSL connections. 
     Further referring to  FIG. 5B , any of the functionality and/or embodiments of the cores  505  described above in connection with  FIG. 5A  can be deployed in any embodiment of the virtualized environment described above in connection with  FIGS. 4A and 4B . Instead of the functionality of the cores  505  being deployed in the form of a physical processor  505 , such functionality may be deployed in a virtualized environment  400  on any computing device  100 , such as a client  102 , server  106  or appliance  200 . In other embodiments, instead of the functionality of the cores  505  being deployed in the form of an appliance or a single device, the functionality may be deployed across multiple devices in any arrangement. For example, one device may comprise two or more cores and another device may comprise two or more cores. For example, a multi-core system may include a cluster of computing devices, a server farm or network of computing devices. In some embodiments, instead of the functionality of the cores  505  being deployed in the form of cores, the functionality may be deployed on a plurality of processors, such as a plurality of single core processors. 
     In one embodiment, the cores  505  may be any type and form of processor. In some embodiments, a core can function substantially similar to any processor or central processing unit described herein. In some embodiment, the cores  505  may comprise any portion of any processor described herein. While  FIG. 5A  illustrates seven cores, there can exist any “N” number of cores within an appliance  200 , where “N” is any whole number greater than one. In some embodiments, the cores  505  can be installed within a common appliance  200 , while in other embodiments the cores  505  can be installed within one or more appliance(s)  200  communicatively connected to one another. The cores  505  can in some embodiments comprise graphics processing software, while in other embodiments the cores  505  provide general processing capabilities. The cores  505  can be installed physically near each other and/or can be communicatively connected to each other. The cores may be connected by any type and form of bus or subsystem physically and/or communicatively coupled to the cores for transferring data between to, from and/or between the cores. 
     While each core  505  can comprise software for communicating with other cores, in some embodiments a core manager (not shown) can facilitate communication between each core  505 . In some embodiments, the kernel may provide core management. The cores may interface or communicate with each other using a variety of interface mechanisms. In some embodiments, core to core messaging may be used to communicate between cores, such as a first core sending a message or data to a second core via a bus or subsystem connecting the cores. In some embodiments, cores may communicate via any type and form of shared memory interface. In one embodiment, there may be one or more memory locations shared among all the cores. In some embodiments, each core may have separate memory locations shared with each other core. For example, a first core may have a first shared memory with a second core and a second share memory with a third core. In some embodiments, cores may communicate via any type of programming or API, such as function calls via the kernel. In some embodiments, the operating system may recognize and support multiple core devices and provide interfaces and API for inter-core communications. 
     The flow distributor  550  can be any application, program, library, script, task, service, process or any type and form of executable instructions executing on any type and form of hardware. In some embodiments, the flow distributor  550  may any design and construction of circuitry to perform any of the operations and functions described herein. In some embodiments, the flow distributor distribute, forwards, routes, controls and/ors manage the distribution of data packets among the cores  505  and/or packet engine or VIPs running on the cores. The flow distributor  550 , in some embodiments, can be referred to as an interface master. In one embodiment, the flow distributor  550  comprises a set of executable instructions executing on a core or processor of the appliance  200 . In another embodiment, the flow distributor  550  comprises a set of executable instructions executing on a computing machine in communication with the appliance  200 . In some embodiments, the flow distributor  550  comprises a set of executable instructions executing on a NIC, such as firmware. In still other embodiments, the flow distributor  550  comprises any combination of software and hardware to distribute data packets among cores or processors. In one embodiment, the flow distributor  550  executes on at least one of the cores  505 A-N, while in other embodiments a separate flow distributor  550  assigned to each core  505 A-N executes on an associated core  505 A-N. The flow distributor may use any type and form of statistical or probabilistic algorithms or decision making to balance the flows across the cores. The hardware of the appliance, such as a NIC, or the kernel may be designed and constructed to support sequential operations across the NICs and/or cores. 
     In embodiments where the system  545  comprises one or more flow distributors  550 , each flow distributor  550  can be associated with a processor  505  or a packet engine  548 . The flow distributors  550  can comprise an interface mechanism that allows each flow distributor  550  to communicate with the other flow distributors  550  executing within the system  545 . In one instance, the one or more flow distributors  550  can determine how to balance load by communicating with each other. This process can operate substantially similarly to the process described above for submitting votes to an arbiter which then determines which flow distributor  550  should receive the load. In other embodiments, a first flow distributor  550 ′ can identify the load on an associated core and determine whether to forward a first data packet to the associated core based on any of the following criteria: the load on the associated core is above a predetermined threshold; the load on the associated core is below a predetermined threshold; the load on the associated core is less than the load on the other cores; or any other metric that can be used to determine where to forward data packets based in part on the amount of load on a processor. 
     The flow distributor  550  can distribute network traffic among the cores  505  according to a distribution, computing or load balancing scheme such as those described herein. In one embodiment, the flow distributor can distribute network traffic according to any one of a functional parallelism distribution scheme  550 , a data parallelism load distribution scheme  540 , a flow-based data parallelism distribution scheme  520 , or any combination of these distribution scheme or any load balancing scheme for distributing load among multiple processors. The flow distributor  550  can therefore act as a load distributor by taking in data packets and distributing them across the processors according to an operative load balancing or distribution scheme. In one embodiment, the flow distributor  550  can comprise one or more operations, functions or logic to determine how to distribute packers, work or load accordingly. In still other embodiments, the flow distributor  550  can comprise one or more sub operations, functions or logic that can identify a source address and a destination address associated with a data packet, and distribute packets accordingly. 
     In some embodiments, the flow distributor  550  can comprise a receive-side scaling (RSS) network driver, module  560  or any type and form of executable instructions which distribute data packets among the one or more cores  505 . The RSS module  560  can comprise any combination of hardware and software, In some embodiments, the RSS module  560  works in conjunction with the flow distributor  550  to distribute data packets across the cores  505 A-N or among multiple processors in a multi-processor network. The RSS module  560  can execute within the NIC  552  in some embodiments, and in other embodiments can execute on any one of the cores  505 . 
     In some embodiments, the RSS module  560  uses the MICROSOFT receive-side-scaling (RSS) scheme. In one embodiment, RSS is a Microsoft Scalable Networking initiative technology that enables receive processing to be balanced across multiple processors in the system while maintaining in-order delivery of the data. The RSS may use any type and form of hashing scheme to determine a core or processor for processing a network packet. 
     The RSS module  560  can apply any type and form hash function such as the Toeplitz hash function. The hash function may be applied to the hash type or any the sequence of values. The hash function may be a secure hash of any security level or is otherwise cryptographically secure. The hash function may use a hash key. The size of the key is dependent upon the hash function. For the Toeplitz hash, the size may be 40 bytes for IPv6 and 16 bytes for IPv4. 
     The hash function may be designed and constructed based on any one or more criteria or design goals. In some embodiments, a hash function may be used that provides an even distribution of hash result for different hash inputs and different hash types, including TCP/IPv4, TCP/IPv6, IPv4, and IPv6 headers. In some embodiments, a hash function may be used that provides a hash result that is evenly distributed when a small number of buckets are present (for example, two or four). In some embodiments, hash function may be used that provides a hash result that is randomly distributed when a large number of buckets were present (for example, 64 buckets). In some embodiments, the hash function is determined based on a level of computational or resource usage. In some embodiments, the hash function is determined based on ease or difficulty of implementing the hash in hardware. In some embodiments, the hash function is determined based on the ease or difficulty of a malicious remote host to send packets that would all hash to the same bucket. 
     The RSS may generate hashes from any type and form of input, such as a sequence of values. This sequence of values can include any portion of the network packet, such as any header, field or payload of network packet, or portions thereof. In some embodiments, the input to the hash may be referred to as a hash type and include any tuples of information associated with a network packet or data flow, such as any of the following: a four tuple comprising at least two IP addresses and two ports; a four tuple comprising any four sets of values; a six tuple; a two tuple; and/or any other sequence of numbers or values. The following are example of hash types that may be used by RSS:
         4-tuple of source TCP Port, source IP version 4 (IPv4) address, destination TCP Port, and destination IPv4 address.   4-tuple of source TCP Port, source IP version 6 (IPv6) address, destination TCP Port, and destination IPv6 address.   2-tuple of source IPv4 address, and destination IPv4 address.   2-tuple of source IPv6 address, and destination IPv6 address.   2-tuple of source IPv6 address, and destination IPv6 address, including support for parsing IPv6 extension headers.       

     The hash result or any portion thereof may used to identify a core or entity, such as a packet engine or VIP, for distributing a network packet. In some embodiments, one or more hash bits or mask are applied to the hash result. The hash bit or mask may be any number of bits or bytes. A NIC may support any number of bits, such as seven bits. The network stack may set the actual number of bits to be used during initialization. The number will be between 1 and 7, inclusive. 
     The hash result may be used to identify the core or entity via any type and form of table, such as a bucket table or indirection table. In some embodiments, the number of hash-result bits are used to index into the table. The range of the hash mask may effectively define the size of the indirection table. Any portion of the hash result or the hast result itself may be used to index the indirection table. The values in the table may identify any of the cores or processor, such as by a core or processor identifier. In some embodiments, all of the cores of the multi-core system are identified in the table. In other embodiments, a port of the cores of the multi-core system are identified in the table. The indirection table may comprise any number of buckets for example 2 to 128 buckets that may be indexed by a hash mask. Each bucket may comprise a range of index values that identify a core or processor. In some embodiments, the flow controller and/or RSS module may rebalance the network rebalance the network load by changing the indirection table. 
     In some embodiments, the multi-core system  575  does not include a RSS driver or RSS module  560 . In some of these embodiments, a software steering module (not shown) or a software embodiment of the RSS module within the system can operate in conjunction with or as part of the flow distributor  550  to steer packets to cores  505  within the multi-core system  575 . 
     The flow distributor  550 , in some embodiments, executes within any module or program on the appliance  200 , on any one of the cores  505  and on any one of the devices or components included within the multi-core system  575 . In some embodiments, the flow distributor  550 ′ can execute on the first core  505 A, while in other embodiments the flow distributor  550 ″ can execute on the NIC  552 . In still other embodiments, an instance of the flow distributor  550 ′ can execute on each core  505  included in the multi-core system  575 . In this embodiment, each instance of the flow distributor  550 ′ can communicate with other instances of the flow distributor  550 ′ to forward packets back and forth across the cores  505 . There exist situations where a response to a request packet may not be processed by the same core, i.e. the first core processes the request while the second core processes the response. In these situations, the instances of the flow distributor  550 ′ can intercept the packet and forward it to the desired or correct core  505 , i.e. a flow distributor instance  550 ′ can forward the response to the first core. Multiple instances of the flow distributor  550 ′ can execute on any number of cores  505  and any combination of cores  505 . 
     The flow distributor may operate responsive to any one or more rules or policies. The rules may identify a core or packet processing engine to receive a network packet, data or data flow. The rules may identify any type and form of tuple information related to a network packet, such as a 4-tuple of source and destination IP address and source and destination ports. Based on a received packet matching the tuple specified by the rule, the flow distributor may forward the packet to a core or packet engine. In some embodiments, the packet is forwarded to a core via shared memory and/or core to core messaging. 
     Although  FIG. 5B  illustrates the flow distributor  550  as executing within the multi-core system  575 , in some embodiments the flow distributor  550  can execute on a computing device or appliance remotely located from the multi-core system  575 . In such an embodiment, the flow distributor  550  can communicate with the multi-core system  575  to take in data packets and distribute the packets across the one or more cores  505 . The flow distributor  550  can, in one embodiment, receive data packets destined for the appliance  200 , apply a distribution scheme to the received data packets and distribute the data packets to the one or more cores  505  of the multi-core system  575 . In one embodiment, the flow distributor  550  can be included in a router or other appliance such that the router can target particular cores  505  by altering meta data associated with each packet so that each packet is targeted towards a sub-node of the multi-core system  575 . In such an embodiment, CISCO&#39;s vn-tag mechanism can be used to alter or tag each packet with the appropriate meta data. 
     Illustrated in  FIG. 5C  is an embodiment of a multi-core system  575  comprising one or more processing cores  505 A-N. In brief overview, one of the cores  505  can be designated as a control core  505 A and can be used as a control plane  570  for the other cores  505 . The other cores may be secondary cores which operate in a data plane while the control core provides the control plane. The cores  505 A-N may share a global cache  580 . While the control core provides a control plane, the other cores in the multi-core system form or provide a data plane. These cores perform data processing functionality on network traffic while the control provides initialization, configuration and control of the multi-core system. 
     Further referring to  FIG. 5C , and in more detail, the cores  505 A-N as well as the control core  505 A can be any processor described herein. Furthermore, the cores  505 A-N and the control core  505 A can be any processor able to function within the system  575  described in  FIG. 5C . Still further, the cores  505 A-N and the control core  505 A can be any core or group of cores described herein. The control core may be a different type of core or processor than the other cores. In some embodiments, the control may operate a different packet engine or have a packet engine configured differently than the packet engines of the other cores. 
     Any portion of the memory of each of the cores may be allocated to or used for a global cache that is shared by the cores. In brief overview, a predetermined percentage or predetermined amount of each of the memory of each core may be used for the global cache. For example, 50% of each memory of each code may be dedicated or allocated to the shared global cache. That is, in the illustrated embodiment, 2 GB of each core excluding the control plane core or core  1  may be used to form a 28 GB shared global cache. The configuration of the control plane such as via the configuration services may determine the amount of memory used for the shared global cache. In some embodiments, each core may provide a different amount of memory for use by the global cache. In other embodiments, any one core may not provide any memory or use the global cache. In some embodiments, any of the cores may also have a local cache in memory not allocated to the global shared memory. Each of the cores may store any portion of network traffic to the global shared cache. Each of the cores may check the cache for any content to use in a request or response. Any of the cores may obtain content from the global shared cache to use in a data flow, request or response. 
     The global cache  580  can be any type and form of memory or storage element, such as any memory or storage element described herein. In some embodiments, the cores  505  may have access to a predetermined amount of memory (i.e. 32 GB or any other memory amount commensurate with the system  575 ). The global cache  580  can be allocated from that predetermined amount of memory while the rest of the available memory can be allocated among the cores  505 . In other embodiments, each core  505  can have a predetermined amount of memory. The global cache  580  can comprise an amount of the memory allocated to each core  505 . This memory amount can be measured in bytes, or can be measured as a percentage of the memory allocated to each core  505 . Thus, the global cache  580  can comprise 1 GB of memory from the memory associated with each core  505 , or can comprise 20 percent or one-half of the memory associated with each core  505 . In some embodiments, only a portion of the cores  505  provide memory to the global cache  580 , while in other embodiments the global cache  580  can comprise memory not allocated to the cores  505 . 
     Each core  505  can use the global cache  580  to store network traffic or cache data. In some embodiments, the packet engines of the core use the global cache to cache and use data stored by the plurality of packet engines. For example, the cache manager of  FIG. 2A  and cache functionality of  FIG. 2B  may use the global cache to share data for acceleration. For example, each of the packet engines may store responses, such as HTML data, to the global cache. Any of the cache managers operating on a core may access the global cache to server caches responses to client requests. 
     In some embodiments, the cores  505  can use the global cache  580  to store a port allocation table which can be used to determine data flow based in part on ports. In other embodiments, the cores  505  can use the global cache  580  to store an address lookup table or any other table or list that can be used by the flow distributor to determine where to direct incoming and outgoing data packets. The cores  505  can, in some embodiments read from and write to cache  580 , while in other embodiments the cores  505  can only read from or write to cache  580 . The cores may use the global cache to perform core to core communications. 
     The global cache  580  may be sectioned into individual memory sections where each section can be dedicated to a particular core  505 . In one embodiment, the control core  505 A can receive a greater amount of available cache, while the other cores  505  can receiving varying amounts or access to the global cache  580 . 
     In some embodiments, the system  575  can comprise a control core  505 A. While  FIG. 5C  illustrates core  1   505 A as the control core, the control core can be any core within the appliance  200  or multi-core system. Further, while only a single control core is depicted, the system  575  can comprise one or more control cores each having a level of control over the system. In some embodiments, one or more control cores can each control a particular aspect of the system  575 . For example, one core can control deciding which distribution scheme to use, while another core can determine the size of the global cache  580 . 
     The control plane of the multi-core system may be the designation and configuration of a core as the dedicated management core or as a master core. This control plane core may provide control, management and coordination of operation and functionality the plurality of cores in the multi-core system. This control plane core may provide control, management and coordination of allocation and use of memory of the system among the plurality of cores in the multi-core system, including initialization and configuration of the same. In some embodiments, the control plane includes the flow distributor for controlling the assignment of data flows to cores and the distribution of network packets to cores based on data flows. In some embodiments, the control plane core runs a packet engine and in other embodiments, the control plane core is dedicated to management and control of the other cores of the system. 
     The control core  505 A can exercise a level of control over the other cores  505  such as determining how much memory should be allocated to each core  505  or determining which core  505  should be assigned to handle a particular function or hardware/software entity. The control core  505 A, in some embodiments, can exercise control over those cores  505  within the control plan  570 . Thus, there can exist processors outside of the control plane  570  which are not controlled by the control core  505 A. Determining the boundaries of the control plane  570  can include maintaining, by the control core  505 A or agent executing within the system  575 , a list of those cores  505  controlled by the control core  505 A. The control core  505 A can control any of the following: initialization of a core; determining when a core is unavailable; re-distributing load to other cores  505  when one core fails; determining which distribution scheme to implement; determining which core should receive network traffic; determining how much cache should be allocated to each core; determining whether to assign a particular function or element to a particular core; determining whether to permit cores to communicate with one another; determining the size of the global cache  580 ; and any other determination of a function, configuration or operation of the cores within the system  575 . 
     F. Systems and Methods for Providing a Distributed Cluster Architecture 
     As discussed in the previous section, to overcome limitations on transistor spacing and CPU speed increases, many CPU manufacturers have incorporated multi-core CPUs to improve performance beyond that capable of even a single, higher speed CPU. Similar or further performance gains may be made by operating a plurality of appliances, either single or multi-core, together as a distributed or clustered appliance. Individual computing devices or appliances may be referred to as nodes of the cluster. A centralized management system may perform load balancing, distribution, configuration, or other tasks to allow the nodes to operate in conjunction as a single computing system. Externally or to other devices, including servers and clients, in many embodiments, the cluster may be viewed as a single virtual appliance or computing device, albeit one with performance exceeding that of a typical individual appliance. 
     Referring now to  FIG. 6 , illustrated is an embodiment of a computing device cluster or appliance cluster  600 . A plurality of appliances  200   a - 200   n  or other computing devices, sometimes referred to as nodes, such as desktop computers, servers, rackmount servers, blade servers, or any other type and form of computing device may be joined into a single appliance cluster  600 . Although referred to as an appliance cluster, in many embodiments, the cluster may operate as an application server, network storage server, backup service, or any other type of computing device without limitation. In many embodiments, the appliance cluster  600  may be used to perform many of the functions of appliances  200 , WAN optimization devices, network acceleration devices, or other devices discussed above. 
     In some embodiments, the appliance cluster  600  may comprise a homogenous set of computing devices, such as identical appliances, blade servers within one or more chassis, desktop or rackmount computing devices, or other devices. In other embodiments, the appliance cluster  600  may comprise a heterogeneous or mixed set of devices, including different models of appliances, mixed appliances and servers, or any other set of computing devices. This may allow for an appliance cluster  600  to be expanded or upgraded over time with new models or devices, for example. 
     In some embodiments, each computing device or appliance  200  of an appliance cluster  600  may comprise a multi-core appliance, as discussed above. In many such embodiments, the core management and flow distribution methods discussed above may be utilized by each individual appliance, in addition to the node management and distribution methods discussed herein. This may be thought of as a two-tier distributed system, with one appliance comprising and distributing data to multiple nodes, and each node comprising and distributing data for processing to multiple cores. Accordingly, in such embodiments, the node distribution system need not manage flow distribution to individual cores, as that may be taken care of by a master or control core as discussed above. 
     In many embodiments, an appliance cluster  600  may be physically grouped, such as a plurality of blade servers in a chassis or plurality of rackmount devices in a single rack, but in other embodiments, the appliance cluster  600  may be distributed in a plurality of chassis, plurality of racks, plurality of rooms in a data center, plurality of data centers, or any other physical arrangement. Accordingly, the appliance cluster  600  may be considered a virtual appliance, grouped via common configuration, management, and purpose, rather than a physical group. 
     In some embodiments, an appliance cluster  600  may be connected to one or more networks  104 ,  104 ′. For example, referring briefly back to  FIG. 1A , in some embodiments, an appliance  200  may be deployed between a network  104  joined to one or more clients  102 , and a network  104 ′ joined to one or more servers  106 . An appliance cluster  600  may be similarly deployed to operate as a single appliance. In many embodiments, this may not require any network topology changes external to appliance cluster  600 , allowing for ease of installation and scalability from a single appliance scenario. In other embodiments, an appliance cluster  600  may be similarly deployed as shown in  FIGS. 1B-1D  or discussed above. In still other embodiments, an appliance cluster may comprise a plurality of virtual machines or processes executed by one or more servers. For example, in one such embodiment, a server farm may execute a plurality of virtual machines, each virtual machine configured as an appliance  200 , and a plurality of the virtual machines acting in concert as an appliance cluster  600 . In yet still other embodiments, an appliance cluster  600  may comprise a mix of appliances  200  or virtual machines configured as appliances  200 . In some embodiments, appliance cluster  600  may be geographically distributed, with the plurality of appliances  200  not co-located. For example, referring back to  FIG. 6 , in one such embodiment, a first appliance  200   a  may be located at a first site, such as a data center and a second appliance  200   b  may be located at a second site, such as a central office or corporate headquarters. In a further embodiment, such geographically remote appliances may be joined by a dedicated network, such as a T1 or T3 point-to-point connection; a VPN; or any other type and form of network. Accordingly, although there may be additional communications latency compared to co-located appliances  200   a - 200   b , there may be advantages in reliability in case of site power failures or communications outages, scalability, or other benefits. In some embodiments, latency issues may be reduced through geographic or network-based distribution of data flows. For example, although configured as an appliance cluster  600 , communications from clients and servers at the corporate headquarters may be directed to the appliance  200   b  deployed at the site, load balancing may be weighted by location, or similar steps can be taken to mitigate any latency. 
     Still referring to  FIG. 6 , an appliance cluster  600  may be connected to a network via a client data plane  602 . In some embodiments, client data plane  602  may comprise a communication network, such as a network  104 , carrying data between clients and appliance cluster  600 . In some embodiments, client data plane  602  may comprise a switch, hub, router, or other network devices bridging an external network  104  and the plurality of appliances  200   a - 200   n  of the appliance cluster  600 . For example, in one such embodiment, a router may be connected to an external network  104 , and connected to a network interface of each appliance  200   a - 200   n . In some embodiments, this router or switch may be referred to as an interface manager, and may further be configured to distribute traffic evenly across the nodes in the application cluster  600 . Thus, in many embodiments, the interface master may comprise a flow distributor external to appliance cluster  600 . In other embodiments, the interface master may comprise one of appliances  200   a - 200   n . For example, a first appliance  200   a  may serve as the interface master, receiving incoming traffic for the appliance cluster  600  and distributing the traffic across each of appliances  200   b - 200   n . In some embodiments, return traffic may similarly flow from each of appliances  200   b - 200   n  via the first appliance  200   a  serving as the interface master. In other embodiments, return traffic from each of appliances  200   b - 200   n  may be transmitted directly to a network  104 ,  104 ′, or via an external router, switch, or other device. In some embodiments, appliances  200  of the appliance cluster not serving as an interface master may be referred to as interface slaves. 
     The interface master may perform load balancing or traffic flow distribution in any of a variety of ways. For example, in some embodiments, the interface master may comprise a router performing equal-cost multi-path (ECMP) routing with next hops configured with appliances or nodes of the cluster. The interface master may use an open-shortest path first (OSPF) In some embodiments, the interface master may use a stateless hash-based mechanism for traffic distribution, such as hashes based on IP address or other packet information tuples, as discussed above. Hash keys and/or salt may be selected for even distribution across the nodes. In other embodiments, the interface master may perform flow distribution via link aggregation (LAG) protocols, or any other type and form of flow distribution, load balancing, and routing. 
     In some embodiments, the appliance cluster  600  may be connected to a network via a server data plane  604 . Similar to client data plane  602 , server data plane  604  may comprise a communication network, such as a network  104 ′, carrying data between servers and appliance cluster  600 . In some embodiments, server data plane  604  may comprise a switch, hub, router, or other network devices bridging an external network  104 ′ and the plurality of appliances  200   a - 200   n  of the appliance cluster  600 . For example, in one such embodiment, a router may be connected to an external network  104 ′, and connected to a network interface of each appliance  200   a - 200   n . In many embodiments, each appliance  200   a - 200   n  may comprise multiple network interfaces, with a first network interface connected to client data plane  602  and a second network interface connected to server data plane  604 . This may provide additional security and prevent direct interface of client and server networks by having appliance cluster  600  server as an intermediary device. In other embodiments, client data plane  602  and server data plane  604  may be merged or combined. For example, appliance cluster  600  may be deployed as a non-intermediary node on a network with clients  102  and servers  106 . As discussed above, in many embodiments, an interface master may be deployed on the server data plane  604 , for routing and distributing communications from the servers and network  104 ′ to each appliance of the appliance cluster. In many embodiments, an interface master for client data plane  602  and an interface master for server data plane  604  may be similarly configured, performing ECMP or LAG protocols as discussed above. 
     In some embodiments, each appliance  200   a - 200   n  in appliance cluster  600  may be connected via an internal communication network or back plane  606 . Back plane  606  may comprise a communication network for inter-node or inter-appliance control and configuration messages, and for inter-node forwarding of traffic. For example, in one embodiment in which a first appliance  200   a  communicates with a client via network  104 , and a second appliance  200   b  communicates with a server via network  104 ′, communications between the client and server may flow from client to first appliance, from first appliance to second appliance via back plane  606 , and from second appliance to server, and vice versa. In other embodiments, back plane  606  may carry configuration messages, such as interface pause or reset commands; policy updates such as filtering or compression policies; status messages such as buffer status, throughput, or error messages; or any other type and form of inter-node communication. In some embodiments, RSS keys or hash keys may be shared by all nodes in the cluster, and may be communicated via back plane  606 . For example, a first node or master node may select an RSS key, such as at startup or boot, and may distribute this key for use by other nodes. In some embodiments, back plane  606  may comprise a network between network interfaces of each appliance  200 , and may comprise a router, switch, or other network device (not illustrated). Thus, in some embodiments and as discussed above, a router for client data plane  602  may be deployed between appliance cluster  600  and network  104 , a router for server data plane  604  may be deployed between appliance cluster  600  and network  104 ′, and a router for back plane  606  may be deployed as part of appliance cluster  600 . Each router may connect to a different network interface of each appliance  200 . In other embodiments, one or more planes  602 - 606  may be combined, or a router or switch may be split into multiple LANs or VLANs to connect to different interfaces of appliances  200   a - 200   n  and serve multiple routing functions simultaneously, to reduce complexity or eliminate extra devices from the system. 
     In some embodiments, a control plane (not illustrated) may communicate configuration and control traffic from an administrator or user to the appliance cluster  600 . In some embodiments, the control plane may be a fourth physical network, while in other embodiments, the control plane may comprise a VPN, tunnel, or communication via one of planes  602 - 606 . Thus, the control plane may, in some embodiments, be considered a virtual communication plane. In other embodiments, an administrator may provide configuration and control through a separate interface, such as a serial communication interface such as RS-232; a USB communication interface; or any other type and form of communication. In some embodiments, an appliance  200  may comprise an interface for administration, such as a front panel with buttons and a display; a web server for configuration via network  104 ,  104 ′ or back plane  606 ; or any other type and form of interface. 
     In some embodiments, as discussed above, appliance cluster  600  may include internal flow distribution. For example, this may be done to allow nodes to join/leave transparently to external devices. To prevent an external flow distributor from needing to be repeatedly reconfigured on such changes, a node or appliance may act as an interface master or distributor for steering network packets to the correct node within the cluster  600 . For example, in some embodiments, when a node leaves the cluster (such as on failure, reset, or similar cases), an external ECMP router may identify the change in nodes, and may rehash all flows to redistribute traffic. This may result in dropping and resetting all connections. The same drop and reset may occur when the node rejoins. In some embodiments, for reliability, two appliances or nodes within appliance cluster  600  may receive communications from external routers via connection mirroring. 
     In many embodiments, flow distribution among nodes of appliance cluster  600  may use any of the methods discussed above for flow distribution among cores of an appliance. For example, in one embodiment, a master appliance, master node, or interface master, may compute a RSS hash, such as a Toeplitz hash on incoming traffic and consult a preference list or distribution table for the hash. In many embodiments, the flow distributor may provide the hash to the recipient appliance when forwarding the traffic. This may eliminate the need for the node to recompute the hash for flow distribution to a core. In many such embodiments, the RSS key used for calculating hashes for distribution among the appliances may comprise the same key as that used for calculating hashes for distribution among the cores, which may be referred to as a global RSS key, allowing for reuse of the calculated hash. In some embodiments, the hash may be computed with input tuples of transport layer headers including port numbers, internet layer headers including IP addresses; or any other packet header information. In some embodiments, packet body information may be utilized for the hash. For example, in one embodiment in which traffic of one protocol is encapsulated within traffic of another protocol, such as lossy UDP traffic encapsulated via a lossless TCP header, the flow distributor may calculate the hash based on the headers of the encapsulated protocol (e.g. UDP headers) rather than the encapsulating protocol (e.g. TCP headers). Similarly, in some embodiments in which packets are encapsulated and encrypted or compressed, the flow distributor may calculate the hash based on the headers of the payload packet after decryption or decompression. In still other embodiments, nodes may have internal IP addresses, such as for configuration or administration purposes. Traffic to these IP addresses need not be hashed and distributed, but rather may be forwarded to the node owning the destination address. For example, an appliance may have a web server or other server running for configuration or administration purposes at an IP address of 1.2.3.4, and, in some embodiments, may register this address with the flow distributor as it&#39;s internal IP address. In other embodiments, the flow distributor may assign internal IP addresses to each node within the appliance cluster  600 . Traffic arriving from external clients or servers, such as a workstation used by an administrator, directed to the internal IP address of the appliance (1.2.3.4) may be forwarded directly, without requiring hashing. 
     G. Systems and Methods for SNMP Caching Across Multi-Core and Clustered Systems. 
     The systems and methods of the present solution illustrated in  FIGS. 7A-7D  are directed to SNMP (Simple Network Management Protocol) caching for multi-core and/or clustered systems, such as a multi-core intermediary device  200  or a clustered system of intermediary devices  600 . The systems and methods of the present solution provide a dynamic SNMP cache that can reliably insert, invalidate, flush and determine cache hit/miss for GETNEXT requests together with GET requests. This cache implementation stores partial cluster/multi-core entities configuration and statistical info with default cache ordering and explicit SNMP lexicographic ordering maintained among these entities. SNMP ordering is used to determine a cache hit for GETNEXT. Partial cache invalidations and deletions are associated with invalidating the SNMP ordering of relevant entities and the cache still works for GET operations over these entities and GETNEXT for other entities with SNMP ordering intact. 
     In some embodiments, the present solution uses a network management protocol, such as SNMP, to query a server or device for one or more objects identifiers and data for the objects of the object identifiers. By way of example only and not in any way limiting, the present solution may use an SNMP architecture to provide management information bases (MIBs), which specify management data of a device or device subsystem, such as a service  270  or virtual server  275 , using a hierarchical namespace containing object identifiers for managed objects. In some embodiments, a MIB is a collection of information that is organized hierarchically. MIBs may be accessed using a network-management protocol such as SNMP. An MIB includes managed objects identified by object identifiers. In one embodiment, a managed object (sometimes called a MIB object, an object, or a MIB) is one of any number of characteristics or metrics of a managed device, appliance or system. In some embodiments, a managed objects includes one or more object instances, which correspond to or referred to as variables. 
     A managed object may include scalar and tabular Objects. A managed object may have both a type (e.g., as defined in ASN.1) and a value. For example, the SNMP system group variable sysLocation (this variable is defined in RFC1213-MIB) has the type, DisplayString and may have the value, “WebNMS”. Managed objects, in SNMP, are of two types: scalar objects and tabular objects. A managed object that always has a single instance is called a scalar object. Tabular objects have multiple instances, such as the rows of a table. Tables in SNMP are two-dimensional objects defined as an ASN.1 type called SEQUENCE OF, which allows 0 or more members. Each element of the sequence is an entry (row) in the table, which itself is a sequence of scalar-valued objects. 
     In one embodiment, the MIB hierarchy may be depicted as a tree with a nameless root, the levels of which are assigned by different organizations. In some embodiments, the top-level MIB object IDs may belong to different standards organizations, while lower-level object IDs are allocated by associated organizations. The MIB and/or objects may be arranged, constructed or organized for management across any of layers of the OSI reference model. In some embodiments, the MIB and/or objects provide managed data and information on applications such as databases, email, and web services. Furthermore, the MIB and/or objects may define for any area-specific or appliance specification information and operations, such as for any type of service  270 , server  106  or device  100  managed by the appliance  200 . 
     In the example embodiment of SNMP, the SNMP communication model is based on a manager and an agent with a data of management information and management objects. In one embodiment, the manager provides an interface to the managed system. The agent provides the interface between the manager and the device, system, application, component, element or resource being managed. As illustrated in  FIG. 7A , the appliance  200  or device may include a manager and/or agent in the form of daemons referred to as snmpd. A manager, such as a master snmpd on a core or node, may requests and obtains object identifiers and values from an agent, such as a non-master snmp executing on a core or node. In the example of SNMP, a manager communicates a GET or GET-NEXT message to request information for a specific object. The agent, in response to the manger&#39;s request, issues a GET-RESPONSE message to the manager with the information requested or an error message. The manager may transmit a SET message to request a change to a value of a specific variable or object. The agent may issue a TRAP message to inform the manager of an event, such as an alarm or error on a service  270  or virtual server. 
     Although generally described in an embodiment of an SNMP network management protocol, the present solution may use any type and form of network management protocol and communication model to obtain identifiers and values of information, such as objects or variables, from another device for an entity, such as a managed system, sub-system, virtual server  275  or service  270 . For example, the appliance  200  may use any of the following protocols and/or communication models: Remote monitoring (RMON), AgentX, Simple Gateway Monitoring Protocol (SGMP), Common management information protocol (CMIP), Common management information service (CMIS) or CMIP over TCP/IP (CMOT). 
     Furthermore, although a MIB is generally described in reference to a manager/agent communication model for an example network management protocol such as SNMP, the MIB may include any type and form of data storage of object identifiers, variables, parameters or other identifiers of metrics. The MIB may be either protocol dependent or protocol independent. For example, the MIB may comprise a table of metrics for a device or service that can be queried via any type and form of API. 
     Although the systems and methods of the present solution may be described in connection with SNMP or other network protocols, these systems and methods are useful and can be used for any implementation or deployment in which variables, objects or tabular data cross multiple cores or nodes is to be cached. 
     Referring now to  FIG. 7A , an embodiment of SNMP caching in a multi-core system is depicted. In brief overview, the system includes a multi-core computing device  100  or intermediary device  200 , such as any embodiments of an appliance described herein. The multi-core device may include a plurality of cores  505 A- 505 N (generally referred to as core  505 ). Each core  505  may execute, operate or comprise a plurality of entities  710 A- 710 N (generally referred to as entity  710 ), such for example a virtual server  275 . Each core  505  may execute or operate a monitoring agent  705 A- 705 N, generally referred to as a snmpd in the embodiments of SNMP deployment or architecture. One of the cores, such as core  505 N, which may be referred to as the master core, may execute or operate an agent manager or master agent  705 N, such as a SNMP agent in embodiments of an SNMP architecture and as identified as SNMPD or Master  705 N in  FIG. 7A . The master core may establish or provide a Management Information Base (MIB)  717 . The master core, such as via SNMPD or Master agent  705 N, may distribute the MIB, or portions thereof, across the cores. The master core and/or each of the cores may have a SNMP cache  730 A- 730 N to store managed objects collected from any of the cores. The appliance may use the information stored in the SNMP cache to respond to SNMP GET and GETNEXT requests from an SNMP Manager  707  executing on a device  100  in communication via a network  104  with the cluster  600 . 
     The device may be any type and form of multi-core device  100 . The device may be any type and form of multi-core device deployed as an intermediary device or appliance  200 . The device may include any embodiments of the multi-core appliance depicted and/or described in connection with  FIGS. 5A-5C . In some embodiments, the multi-core device may operate or execute a packet processing engine or packet engine on each core of the multi-core device. In some embodiments, the multi-core device may operate or execute a virtual server on each core of the multi-core device. 
     Each agent on each core may monitor values  712 A- 712 N (generally referred to as monitored values  712 ) in connection with, associated with or for one or more entities. These entities may be represented by managed objects in the SNMP model and stored in the MIB  717 . In some embodiments, the managed object for the entity may be a scalar data type. In some embodiments, the managed object for the entity may be a tabular data type. The master agent  705 N may communicate with each core or agent to obtain the monitored values for the entity and stores these values to the MIB. The agents may communicate with the master agent to store these values to the MIB. The SNMP caches on each core may communicate monitored entity data with each other. The SNMP caches on non-master cores may communicate cached data to the SNMP cache on the master core. 
     In further details, the entity to be monitored or managed may comprise any executable, service, process, module, component, data parameter or other information produced or provided via the system, such as any embodiments of the appliance  200  described herein. In some embodiments, the entity comprises any elements, components or modules of the appliance identified and described in connection with  FIG. 2A . In some embodiments, the entity comprises the packet processing engine. In some embodiments, the entity comprises any elements, components or modules of the appliance identified and described in connection with  FIG. 2N . In some embodiments, the entity comprises a virtual server  275 . In some embodiments, the entity comprises a server  270  managed by a virtual server or the appliance. In some embodiments, the entity comprises a client agent  120 . In some embodiments, the entity comprises a service or servicegroup. In some embodiments, the entity comprises a core. In some embodiments, the entity comprises a virtualized environment. In some embodiments, the entity comprises a virtual machine. In some embodiments, the entity comprises an interface slave  610 . In some embodiments, the entity comprises an interface master  608 . In some embodiments, the number of entities monitored by the appliance or cluster may exceed a predetermined threshold, such as 100,000. 
     In some embodiments, each entity of a plurality of entities to be monitored or managed may be distributed or allocated among the cores in a multi-core device. Each core may designated an owner core of, or otherwise a core responsible for, a set of one or more entities of the plurality of entities. Likewise, each entity of a plurality of entities to be monitored or managed may be distributed or allocated among the nodes in a cluster. Each node may designated an owner node of, or otherwise a core responsible for, a set of one or more entities of the plurality of entities. 
     The monitored value  712  may be a value of any metric, parameter or attribute of or associated with the entity. For example, in embodiments of a virtual server, the monitored value may be any operational or performance metric, parameters or attribute of the virtual server. The monitored value may be a number of connections. The monitored value may be a number of connections. The monitored value may be a number of connections. The monitored value may be a number of clients. The monitored value may be bandwidth used by the virtual server. The monitored value may be throughput of the virtual server. The monitored value may be number of packets sent and/or received by the virtual server or to/from a service. The monitored value may be the response time of a server or service. 
     The agents  705  may comprise any type and form of executable instructions executing on a processor, core or device. In some embodiments, the agent may be a virtual machine operating in a virtualized environment provided by the appliance  200 . In some embodiments, the agent may be incorporated, integrated or otherwise a part of any embodiments of a packet processing engine or virtual server described herein. In embodiments of an SNMP architecture, the agent  705  may comprise a SNMP polling or monitor daemon referred to as an snmpd. An agent may be configured, constructed or implemented to identify, collect and/or monitor monitored values of an entity An agent may obtain monitored values from an entity via an API or interface to the entity. An agent may be configured, constructed or implemented to identify, collect and/or monitor monitored values an entity via a network management protocol, such as SNMP. An agent may obtain monitored values from an entity via an SNMP database or MIB. Each of the agents may communicate with each other and/or the master agent using a proprietary protocol, interface or mechanism. Each of the agents may communicate with each other and/or the master agent via core to core messaging or interfacing. 
     The master agent  705 N may comprise any type and form of executable instructions executing on a processor, core or device. In embodiments of an SNMP architecture, the master agent  705 N may comprise an SNMP based manager or agent. The manager, in some embodiment, may be in the form of a daemon referred to as an snmpd. In some embodiments, the master agent may be incorporated, integrated or otherwise a part of any embodiments of a packet processing engine or virtual server described herein. The master agent  705 N may comprise any embodiments of the agent. In a multi-core system, the master agent may operate one or more cores. In some embodiments, the master agent executes or operates on a designated core or a core identified or designated as a master core. 
     Each core may communicate with another core via inter-core communications  720 . Inter-core communications may include core to core messaging. Inter-core communications may include reading and/or writing to a shared memory. The master agent or SNMPD may communicate with agents on each of the cores or other cores in a multi-core device via an inter-core communication  720 . The SNMP cache on a master core may communicate with SNMP caches on each of the cores or other cores in a multi-core device via an inter-core communication  720 . Any component on one core, such as a packet engine, may communicate with another component on another core via an inter-core communication. 
     The SNMP cache  730 , sometime generally referred to as a cache, may include software, hardware or any combination of software and hardware to store data, information and objects to a cache in memory or storage, provide cache access, and control and manage the cache. The data, objects or content processed and stored by the SNMP cache may include data in any format, such as data for the SNMP protocol and/or MIB  717 . In some embodiments, the SNMP cache is designed and constructed for SNMP based data, such as data for managed objects and data for responding to SNMP GET and GETNEXT requests. In some embodiments, the SNMP cache duplicates original data stored elsewhere or data previously computed, generated or transmitted, in which the original data may require longer access time to fetch, compute or otherwise obtain relative to reading a cache memory or storage element. Once the data is stored in the cache, future use can be made by accessing the cached copy rather than refetching or recomputing the original data, thereby reducing the access time. In some embodiments, the cache may comprise a data object in memory of the appliance  200 . In another embodiment, the cache may comprise any type and form of storage element of the appliance  200 , such as a portion of a hard disk. In some embodiments, the processing unit of the device may provide cache memory for use by the SNMP cache. In yet further embodiments, the SNMP cache may use any portion and combination of memory, storage, or the processing unit for caching data, objects, and other content. 
     In some embodiments, the SNMP cache is distributed among the cores in a multi-core device. Each core may maintain a SNMP cache. Each core, such as via agent  705 , may store values for a managed object, such as for an entity, that is managed by each of the cores. Each core may maintain a SNMP cache for those entities for which the core is the owner core. Each core, such as via agent  705 , may store values to the MIB for a managed object, such as for an entity, that is managed by each of the cores. Each core may maintain a portion of the SNMP cache of the master core while the master core maintains an aggregate of SNMP cache data in the SNMP cache on the master core. In some embodiments, one SNMP cache may operate on the master core that receives SNMP cache data from each of the cores. In some embodiments, the SNMP cache may operate on the master core and receives SNMP cache data from the MIB. 
     The appliance  200 , such as via master agent  705  may communicate with a SNMP manager  707  via a network  104 . In embodiments of an SNMP architecture, SNMP uses, one or more administrative computers, called managers  707 , which have the task of monitoring or managing a group of hosts or devices on a network. Each managed system, such as appliance  200  or cluster  600 , may execute a master agent or snmpd  705  which reports information via SNMP to the SNMP manager  707 . The SNMP manager may be an external device or may be a software component executing on a device  100  in communication via a network with the appliance, which is or acts as the SNMP agent. 
     In operation, each of the agents may monitor the monitored values  720  of an entity. Each of the agents may query or poll the monitored value on a predetermined frequency. Each of the agents may query or poll the monitored value via an API to the entity. Each of the agents may query or poll the monitored value via the SNMP protocol. Each of the agents may store, insert or collect the monitored value(s) via the SNMP protocol to an MIB or SNMP database. These monitored values may correspond to or be represented by managed SNMP objects having object identifiers (OIDs) and stored in a MIB. 
     The SNMP cache(s) may obtain managed object data from the agents. In some embodiments, the SNMP cache fetches or prefetches managed object data from the agents. In some embodiments, the SNMP cache may obtain managed object data from the MIB. In some embodiments, the SNMP cache fetches or prefetches managed object data from the MIB. In some embodiments, as a core, such as a packet engine executing on the core, responds to a SNMP GET or GETNEXT request, the response or portions thereof are stored to the SNMP cache. 
     Responsive to receipt of a SNMP GET or GETNEXT request, such as from the SNMP manager  707 , the master agent may query, poll or obtain the monitored values from each of the agents. In some embodiments, the master agent may use SNMP protocol communications to obtain, query or poll the monitored value of the entity from agent(s) monitoring the entity. In some embodiments, the master agent may use SNMP protocol communications to obtain, query or poll the monitored value of the entity from the entity. In some embodiments, the master agent may use SNMP protocol communications to obtain, query or poll the monitored value of the entity from a SNMP database or MIB. In some embodiments, the master agent may use proprietary protocol communications or interface to obtain, query or poll the monitored value of the entity from an agent. The SNMP cache may store the monitored values, such as responsive to the master agent. Responsive to a SNMP GET or GETNEXT request, the core may respond to the request with data stored in the SNMP cache. For example, the master agent on the core may send an SNMP response to the SNMP manager over the network. 
     Referring now to  FIG. 7B , an embodiment of SNMP caching in a clustered system is depicted. In brief overview, the system includes multiple intermediary devices  200 , such as any embodiments of an appliance  200  described herein, designed, constructed and/or deployed into a cluster  600  as described in connection with  FIG. 6 . The cluster may include a plurality of appliances  200 A- 200 N (generally referred to as appliance  200 ). Each appliance may be considered a node in a multi-node cluster  600 . Each appliance  200  may execute, operate or comprise a plurality of entities  710 A- 710 N (generally referred to as entity  710 ), such as, for example, a virtual server  275 . Each appliance may execute or operate a monitoring agent  705 A- 705 N, generally referred to as a snmpd in the embodiments of SNMP deployment or architecture. One of the appliances, such as appliance  200 N, which may be referred to as the master node, may execute or operate a snmpd or master agent  705 N, such as a SNMP agent and/or manager in embodiments of an SNMP architecture and as identified as SNMPD Master  705 N in  FIG. 7A . The master node and/or each of the nodes may have a SNMP cache  730 A- 730 N to store managed objects collected from any of the nodes. The cluster may use the information stored in the SNMP cache(s) to respond to SNMP GET and GETNEXT requests, such as requested by an SNMP Manager  707  on a device  100  in communication with the cluster  600  via a network  104 . 
     In some embodiments, each appliance in the cluster may be a single processor appliance. In some embodiments, each appliance in the cluster may be a multi-core device. In the clustered system, each appliance may communicate with another appliance via a data plane, such as back plane  606  described in connection with  FIG. 6 . Each appliance may communicate with other appliances via a data plane or black plane using an interface slave  610 . One of the appliances in the cluster  600  may be designated or identified as a master node or appliance. The master node or appliance may execute an interface master  608  for coordinating and managing the cluster. 
     The cluster  200 , such as via master agent  705  may communicate with a SNMP manager  707  via a network  104 . A cluster  600 , may execute a master agent or snmpd  705  which reports information via SNMP to the SNMP manager  707 . 
     Each agent on each appliance (e.g., node) may monitor values  712 A- 712 N (generally referred to as monitored values  712 ) in connection with, associated with or for one or more entities. These entities may be represented by managed objects, such as scalar and tabular data types, in the SNMP model and stored in the MIB  717 . The master agent  705 N may communicate with each node or agent to obtain the monitored values for the entity and stores these values to the MIB. The agents may communicate with the master agent to store these values to the MIB. SNMP caches on each node may communicate monitored entity data with each node. SNMP caches on non-master nodes may communicate cached data to the SNMP cache on the master node. 
     In some embodiments, the SNMP cache is distributed among the nodes in the cluster  600 . Each node may maintain a SNMP cache. Each node, such as via agent  705 , may store values for a managed object, such as for an entity, that is managed by each of the nodes. Each node may maintain a SNMP cache for those entities for which the node is the owner node. Each node, such as via agent  705 , may store values to the MIB for a managed object, such as for an entity, that is managed by each of the nodes. Each node may maintain a portion of the SNMP cache of the master node while the master node maintains an aggregate of SNMP cache data in the SNMP cache on the master node. In some embodiments, one SNMP cache may operate on the master node that receives SNMP cache data from each of the nodes. In some embodiments, the SNMP cache may operate on the master node and receives SNMP cache data from the MIB. 
     In operation and in some embodiments, the agents on each appliance communicate with the master on the master node or appliance via the backplane. In some embodiments, the agents on each appliance communicate with the master on the master node or appliance via network communications. In some embodiments, the agents on each appliance communicate via the interface slave with the master agent via interface master on the master node or appliance. Each appliance may establish a connection, such as a transport layer connection, with the other appliances. Each agent on each appliance may establish a connection, such as a transport layer connection, with the master agent on the master node or appliance. Using any of the above communication mechanisms, agents of appliances can communicate SNMP cache data and/or monitored values to the master agent or SNMP cache on the master node and the master node may query or request monitored values from the agents. 
     The SNMP cache(s) may obtain managed object data from the agents executing on the appliances. In some embodiments, the SNMP cache fetches or prefetches managed object data from the agents. In some embodiments, the SNMP cache may obtain managed object data from the MIB. In some embodiments, the SNMP cache fetches or prefetches managed object data from the MIB. In some embodiments, as a appliance, such as a packet engine executing on the appliance in the cluster, responds to a SNMP GET or GETNEXT request, the response or portions thereof are stored to the SNMP cache. 
     Responsive to receipt of a SNMP GET or GETNEXT request, such as from the SNMP Manager  707 , the master agent may query, poll or obtain the monitored values from each of the agents. In some embodiments, the master agent may use SNMP protocol communications to obtain, query or poll the monitored value of the entity from agent(s) monitoring the entity. In some embodiments, the master agent may use SNMP protocol communications to obtain, query or poll the monitored value of the entity from the entity. In some embodiments, the master agent may use SNMP protocol communications to obtain, query or poll the monitored value of the entity from a SNMP database or MIB. In some embodiments, the master agent may use proprietary protocols, interfaces and/or mechanisms to obtain, query or poll the monitored value of the entity from the agents. The SNMP cache may store the monitored values, such as responsive to the master agent. Responsive to a SNMP GET or GETNEXT request, the appliance or node may respond to the request with data stored in the SNMP cache. For example, the master agent may send an SNMP response, based on cached data in the SNMP cache, to the SNMP manager. 
     Referring to  FIG. 7C , embodiments of the SNMP cache is depicted. In brief overview, an SNMP cache  730  includes a cache manager  740 , which manages the caching of a plurality of managed objects for or representing entities  734 A- 734 N (generally referred to as entities in the cache). Each of the entities may have one or more next entities  735 A- 735 N, such as a next object id (OID) in a tree or sub-tree of a SNMP based MIB. The cache manager  740  may establish and manage cache ordering  742  of entities and next entities in the cache, such as based on OID ordering. The SNMP cache may include an auxiliary cache  732  of a predetermined size which stores one or more last accessed entity pointers  733 , which may point to entity entries in the main cache  730 . The SNMP cache, such as via cache manager, may perform prefetching or augmentation  745  of the cache to setup or maintain cache data. The SNMP cache may perform SNMP Get or GetNext requests to a plurality of SNMP agents or other SNMP caches to obtain managed object data to cache from responses to such requests. As the SNMP cache receives or the core or node having the SNMP cache processes an SNMP GET or GETNEXT request, a response may be served from cache managed object or entity data in the SNMP cache. 
     In further details, the cache manager  740  comprises any type and form of executable instructions executing on a processor or device to manage a cache. The cache manager may include any logic, functions, rules, or operations to perform any caching techniques of the appliance  200 . In some embodiments, the cache manager may operate as an application, library, program, service, process, thread or task. In some embodiments, the cache manager can comprise any type of general purpose processor (GPP), or any other type of integrated circuit, such as a Field Programmable Gate Array (FPGA), Programmable Logic Device (PLD), or Application Specific Integrated Circuit (ASIC). 
     The cache manager may include logic, functions, rules, or operations designed and constructed to manage caching of SNMP based data, such as entities represented by SNMP based objects. The cache manager may store objects in the SNMP cache according to or based on object identifiers (OIDs). An object identifier or OID is an identifier used to name an object, such as an object representing an entity. Structurally, an OID may consist of a node in a hierarchically-assigned namespace, formally defined using the ITU-T&#39;s ASN.1 standard. Successive numbers of the nodes, starting at the root of the tree, identify each node in the tree. Designers set up new nodes by registering them under the node&#39;s registration authority. An SNMP OID (object identifier) may be assigned to an individual object within a Management Information Base (MIB). An MIB can be broken down into a tree structure. Within this structure, individual OIDs are representative of the leaves on the tree. More specifically, an SNMP OID may be a string of numbers, such as 1.3.6.1.4.1.2681.1.2.102. 
     The cache manager may store entities  734 A- 734 N (generally  734 ) and next entities  735 A- 735 N (generally  735 ) in the SNMP cache. An entity may be or may be represented by a managed object identified by an OID and corresponding one or more properties, such as a value. A next entity may be or may be represented by a next instance of managed object in a branch of a tree identified by an OID and corresponding one or more properties, such as a value. The cache manager may store objects in the SNMP cache according to or based on the properties of the managed object, such as in the MIB. The cache manager may store values for these properties in accordance with property or object definitions of the MIB. The objects and property may be arranged and organized in a tree. Each branch of the tree may have a number and a name, and the complete path from the top of the tree down to the point of interest forms the name of that point. This name of that point is an OID. Nodes near the top of the tree may be general in nature. As one moves further down, the names get more and more specific, until one gets to the bottom, where each node represents a particular feature on a specific device (or agent). 
     The cache manager may store entity information, such as an OID and corresponding properties, according to a predetermined ordering  742 . The predetermined ordering may be based on the hierarchy or tree(s) of the MIB. The predetermined ordering may be based on lexicographic OID ordering. The cache manager may maintain or establish the predetermined ordering by providing or using dummy entries to hold to be determined values for an OID. 
     The cache manager may allocate and arrange memory or storage for the cache to support, correspond or implement the hierarchy of an MIB or OID ordering. For example, the cache manager may allocate for each branch of a tree in the hierarchy a predetermined area of memory or storage. The cache manager may store in memory or storage the cache entries in order or arrangement in accordance with the hierarchy and/or OID ordering. For example, the cache manager may store the next OID cache entity  735  adjacent to or subsequent to the storage of a current OID entity  734 . Further to the example, the cache manager may store a sequence of OID entities  734  and next entities  735  for a branch of a tree. 
     The cache manager may be designed and constructed to store and manage values in the SNMP cache for scalar type managed objects. The cache manager may be designed and constructed to store and manage values in the SNMP cache for tabular managed objects, which may comprise rows of values for an entity or entities. As the same entity may managed by a plurality of cores in a multi-core device or a plurality of nodes in a cluster, the cache manager may receive multiple values for the entity from different cores and/or nodes. The cache manager may be designed and constructed to store and manage values for managed objects received from a plurality of cores in a multi-core device. The cache manager may be designed and constructed to store and manage values for managed objects received from a plurality of nodes in a cluster. 
     The cache manager may insert, invalidate, flush and determine cache hits or miss for OIDs requested by GET or GETNEXT requests. For a GETNEXT request, a response is expected by the requestor for the next SNMP object instance value in lexicographic OID order, which may be the statistic or stat of the next entity. As the SNMP cache and cache manager orders OID lexicographically, the cache may efficiently obtain and respond with the next SNMP entity or object instance. In some embodiments, the SNMP cache and cache manager are implemented to store partial cluster or core entities config/stat info with a predetermined cache ordering and explicit SNMP lexicographic ordering maintained among these entities. SNMP ordering may be used to determine a cache hit for GETNEXT. A cache hit includes capability of determining whether an entity is not present at all in the system. In certain cases, the cache manager may insert dummy entity for marking the start and end of the SNMP ordering. All partial invalidations and deletions are associated with invalidating the SNMP ordering of relevant entities and cache still works for GET operations over these entities and GETNEXT for other entities with SNMP ordering intact. 
     In some embodiments, further performance improvements may obtained by having an additional cache on top of the existing cache. The additional or auxiliary cache  732  may comprise a memory or storage cache of a predetermined size, which may be smaller than the main SNMP cache. The cache manager  740  may establish, operate and manage the auxiliary cache  732 . The auxiliary cache  732  may store a predetermined number of entity pointers  733 . An entity pointer may comprise a memory or address pointer, an object identifier or other index to the entity  734  stored in the main SNMP cache. The auxiliary cache  732  may store entity pointers for a predetermined number of entities last accessed in the SNMP cache. The auxiliary cache  732  may store entity pointers for entities that were last accessed in the SNMP cache over a predetermined time period. This auxiliary cache may ensure a high hit ratio for repeated SNMP GETNEXT request (e.g., SNMP WALK operation) by caching last accessed entities within the main cache. This auxiliary cache also aids in insertion in the larger main cache by maintaining pointers to last accessed entity before the main cache miss. 
     In operation, the cache manager  730  may prefetch or augment  745  the SNMP cache by prefetching entity information. The cache manager may be designed and constructed to prefetch entity information upon initialization or establishing of the SNMP cache. The cache manager may be designed and constructed to prefetch entity information responsive to a predetermined schedule or frequency. The cache manager may be designed and constructed to prefetch entity information responsive to a cache miss. The cache manager may be designed and constructed to prefetch entity information responsive to receipt of a SNMP GET or GETNEXT request. The cache manager may be designed and constructed to perform and SNMP WALK operation and fetch an entity and sequence of one or more next entities. The cache manager may use the SNMP protocol and communicate with one or more agents, such as agents on cores or nodes, to prefetch entity information. The cache manager may order the prefetch data in the SNMP cache in accordance with embodiments of cache ordering  742 . 
     A multi-core device or appliance in a cluster may receive a SNMP GET or GETNEXT request. Using the OID from the request, the device or appliance can check or query the SNMP cache for a cache hit. If there is a cache hit, the device or appliance may generate or server a response to the request using the cached data in the SNMP cache. If there is a cache hit, the device or appliance may query the MIB, an agent on a core, an agent on a node to obtain the requested information and generate and serve a response. 
     Referring now to  FIG. 7D , an embodiment of a method of SNMP caching is depicted. In brief overview, at step  750 , a device establishes an SNMP cache and prefetch or augment the SNMP cache. At step  755 , the device may receive a SNMP GET or GETNEXT request. At step  760 , the device determines whether or not a response can be served from SNMP cache. If there is a cache hit, the device serves the response from the SNMP cache. If there is a cache miss, the device obtains the requested information and generates and serves the response. At step  765 , the device performance cache management to maintain SNMP cache, such as cache ordering and entity invalidation or deletion, partially or otherwise. 
     In further details, at step  750 , a device may establish an SNMP cache. In some embodiments, a multi-core device, such as a multi-core appliance  200 , establishes a SNMP cache. The SNMP cache may be established on a master core of the multi-core device. A plurality of SNMP caches may be established or distributed across a plurality of cores of the multi-core device. In some embodiments, a cluster  600 , such as a cluster of appliances, establishes a SNMP cache. The SNMP cache may be established on a master node of the cluster. A plurality of SNMP caches may be established or distributed across a plurality of nodes of the cluster. In some embodiments, the SNMP cache is established with an auxiliary cache. The cache manager may store one or more pointers to entries in the SNMP cache. The cache manager may maintain in the auxiliary cache one or more pointers to the managed objects that were last accessed in the SNMP cache over a predetermined time period. In some embodiments, the SNMP cache is established without an auxiliary cache. 
     The SNMP cache may be augmented with prefetched managed object or entity data. Upon establishing the SNMP cache, the cache manager may fetch managed objects from agents, entities or the MIB. The cache manager may issue one or more GET and/or GETNEXT requests to an SNMP agent or manager to obtain managed object information for an entity. The cache manager may issue one or more GET and/or GETNEXT requests responsive to a predetermined list of objects or OIDs. The cache manager may fetch a managed object responsive to a cache miss. The cache manager may fetch one or more managed objects or OIDs responsive to a GET or GETNEXT request. The device or cache manager may receive a GET request for an object identifiers Responsive to a SNMP GET request, the cache manager may transmit one or more SNMP GETNEXT requests to the one or more managed information bases for one or more managed objects next in the lexicographical order, such as relative to the object identifier of the GET request. The cache manager may fetch one or more managed objects or OIDs on a predetermined schedule or frequency. 
     The SNMP cache may store managed objects in a predetermined lexicographic order. A cache manager for the SNMP cache may order the managed objects in the cache by the predetermined lexicographic order based on their corresponding object identifiers. The SNMP cache may be established on a device intermediary to a plurality of clients and a plurality of servers. The device may respond to SNMP GET and GETNEXT requests with managed objects stored in the SNMP cache. 
     At step  755 , the device may receive a request for an object. The request may identify the object by an OID. The request may identify a next instance of an object by the OID of the current object or object preceding the requested object. The request may be an SNMP GET request. The request may be an SNMP GETNEXT request. The request may comprise any type and form of protocol, such as a network management protocol and is not limited to SNMP. In some embodiments, the request is requested by an SNMP manager  707 . For example, the SNMP manager may send a GET or GETNEXT request to the master agent/snmpd. 
     In some embodiments, a core of a multi-core device receives the request. The receiving core may process the request. In some embodiments, the receiving core may forward the request to a core that owns or is responsible for the entity or managed object. In some embodiments, the receiving core may forward the request to the master core. In some embodiments, the flow distributor of the device determines the core to forward or process the request. 
     In some embodiments, a node in a cluster receives the request. The receiving node may process the request. In some embodiments, the receiving node may forward the request to a node that owns or is responsible for the entity or managed object. In some embodiments, the receiving node may forward the request to the master node. In some embodiments, the interface manager of the cluster determines the node to forward or process the request. 
     At step  760 , the device determines whether or not a response can be served from the SNMP cache. The device, such as a core of a multi-core device or node of a cluster, may determine whether or not the entity identified by the OID of the request is stored in the cache. In some embodiments, the cache manager checks or uses the auxiliary cache to determine if the requested entity or OID has been recently accessed or is otherwise stored in the main cache. For a GET request, the device, such as via the cache manager, may determine if there is cache data for the entity or object identified by the OID of the request. In some embodiments, the cache manager may use the OID as an index to the cache. For a GETNEXT request, the device, such as via the cache manager, may determine if there is cache data for the entity or object identified by the next OID from the OID of the request. In some embodiments, the cache manager may use the OID or the next OID as an index to the cache. For a GET request, the device, such as via the cache manager, may determine if there is cache data for the entity or object identified by the OID of the request. In some embodiments, the cache manager may use the OID as an index to the cache. 
     If there is a cache hit, the device serves the response from the SNMP cache. The device may generate an SNMP response based on cached data in the SNMP cache. The SNMP may obtain the SNMP response from cached data in the SNMP cache. The device may send the SNMP response to the requestor, such as the SNMP manager  707 . If there is a cache miss, the device obtains the requested information and generates and serves the response. The device may query an agent on a core or node to obtain the requested information. The device may query the MIB to obtain the requested information. The device may query the master agent/snmpd for the requested information. The device may generate the SNMP response and send the SNMP response to the requestor, such as the SNMP manager. The device may store the obtained/requested information and/or SNMP response (or portions thereof) to the SNMP cache. 
     At step  765 , the cache manager may perform cache management on the SNMP cache. The cache manager may add, delete and modify entities in the SNMP cache while maintaining the cache ordering, such as OID based ordering. The cache manager may insert entity entries, such as next entities, in a sequence of entities along a branch of a tree into the cache. As the cache manager obtains values for a tabular managed objects, such as sequences of values, the cache manager may insert, add or modify the SNMP cache to include these new sequence of values in association, connection or as part of the managed object or entity entries in the cache. Based on expiration or invalidation management, the cache manager may invalidate or expire portions of a managed object in the cache, such as portions of a sequence of values for a tabular managed object. 
     In some embodiments, the cache manager may insert a dummy entity for marking the start and end of the SNMP ordering. In some embodiments, the cache manager may invalidate certain SNMP order of relevant entities responsive to partial invalidations and deletions associated with the entity. The cache still works for GET operations over these entities with invalid SNMP ordering and GETNEXT still works for other entities with SNMP ordering intact. 
     It should be understood that the systems described above may provide multiple ones of any or each of those components and these components may be provided on either a standalone machine or, in some embodiments, on multiple machines in a distributed system. The systems and methods described above may be implemented as a method, apparatus or article of manufacture using programming and/or engineering techniques to produce software, firmware, hardware, or any combination thereof. In addition, the systems and methods described above may be provided as one or more computer-readable programs embodied on or in one or more articles of manufacture. The term “article of manufacture” as used herein is intended to encompass code or logic accessible from and embedded in one or more computer-readable devices, firmware, programmable logic, memory devices (e.g., EEPROMs, ROMs, PROMs, RAMs, SRAMs, etc.), hardware (e.g., integrated circuit chip, Field Programmable Gate Array (FPGA), Application Specific Integrated Circuit (ASIC), etc.), electronic devices, a computer readable non-volatile storage unit (e.g., CD-ROM, floppy disk, hard disk drive, etc.). The article of manufacture may be accessible from a file server providing access to the computer-readable programs via a network transmission line, wireless transmission media, signals propagating through space, radio waves, infrared signals, etc. The article of manufacture may be a flash memory card or a magnetic tape. The article of manufacture includes hardware logic as well as software or programmable code embedded in a computer readable medium that is executed by a processor. In general, the computer-readable programs may be implemented in any programming language, such as LISP, PERL, C, C++, C#, PROLOG, or in any byte code language such as JAVA. The software programs may be stored on or in one or more articles of manufacture as object code. 
     While various embodiments of the methods and systems have been described, these embodiments are exemplary and in no way limit the scope of the described methods or systems. Those having skill in the relevant art can effect changes to form and details of the described methods and systems without departing from the broadest scope of the described methods and systems. Thus, the scope of the methods and systems described herein should not be limited by any of the exemplary embodiments and should be defined in accordance with the accompanying claims and their equivalents.