Abstract:
Techniques are disclosed for providing mapping of application components to a set of resources in a distributed environment using capacity driven provisioning using a layered approach. By way of example, a method for allocating resources to an application comprises the following steps. A first data structure is obtained representing a post order traversal of a dependency graph for the application and associated containers with capacity requirements. A second data structure is obtained representing a set of resources, and associated with each resource is a tuple representing available capacity. A mapping of the dependency graph data structure to the resource set is generated based on the available capacity such that resources of the set of resources are allocated to the application.

Description:
FIELD OF THE INVENTION 
       [0001]    The present invention relates to computer network management and, more particularly, to techniques for providing mapping of application components to a set of resources in a distributed environment using capacity driven provisioning using a layered approach. 
       BACKGROUND OF THE INVENTION 
       [0002]    With the increasing popularity of Service Oriented Architecture (SOA) based approaches for designing and deploying applications, there is a need to map and deploy composite enterprise applications across a set of resources in a distributed environment. The process of mapping involves verifying that requisite software needed to run the application components is preinstalled on the resources, and the physical resources assigned to the software components have the required capacity to host the software components without compromising the service level agreements (SLA) associated with the composite application. Further, each prerequisite software component could have additional dependencies that need to be met before the software component itself can be installed. For example, these dependencies comprise dependencies on systems libraries, third-part software, and/or operating system components. For example, installation of IBM WebSphere Portal Server requires the installation of IBM WebSphere Application Server. 
         [0003]    Existing approaches to the mapping the composite enterprise applications in a distributed environment take into account raw physical capacity (e.g., memory, network bandwidth, central processing unit). The main weakness of these approaches is that they fail to take into account software component specific dependencies in making the mapping decision. 
       SUMMARY OF THE INVENTION 
       [0004]    Principles of the invention provide techniques for providing mapping of application components to a set of resources in a distributed environment using capacity driven provisioning using a layered approach. 
         [0005]    By way of example, in one embodiment, a method for representing available capacity of a computing resource as a tuple comprises the following steps. A set of one or more software and hardware components installed on the computing resource is obtained. The available capacity for each one of the set of one or more software and hardware components that can act as a container for other components is determined. A tuple is created representing the collection of available capacities for each container. The container may include at least one of: (i) one or more physical resources; (ii) one or more virtual resources; and (iii) one or more nested software containers. 
         [0006]    By way of further example, in another embodiment, a method for allocating resources to an application comprises the following steps. A first data structure is obtained representing a post order traversal of a dependency graph for the application and associated containers with capacity requirements. A second data structure is obtained representing a set of resources, and associated with each resource is a tuple representing available capacity. A mapping of the dependency graph data structure to the resource set is generated based on the available capacity such that resources of the set of resources are allocated to the application. 
         [0007]    These and other objects, features, and advantages of the present invention will become apparent from the following detailed description of illustrative embodiments thereof, which is to be read in connection with the accompanying drawings. 
     
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
         [0008]      FIG. 1  depicts a pictorial representation of a network data processing system, which may be used to implement an exemplary embodiment of the present invention. 
           [0009]      FIG. 2  is a block diagram of a data processing system, which may be used to implement an exemplary embodiment of the present invention. 
           [0010]      FIG. 3  depicts a schematic representation of a service delivery environment, which may be used to implement an exemplary embodiment of the present invention. 
           [0011]      FIG. 4  depicts an example of a logical application structure containing a resource dependency characterization of a sample application, according to an exemplary embodiment of the present invention. 
           [0012]      FIG. 5  shows the logical architecture of the placement controller component, according to an exemplary embodiment of the present invention. 
           [0013]      FIG. 6  shows the steps that the placement controller takes to determine the mapping of a composite business solution (CBS) to a set of resources in a distributed environment, according to an exemplary embodiment of the present invention. 
           [0014]      FIG. 7A  shows the metadata data structure associated with each solution stored in the solution repository, according to an exemplary embodiment of the present invention. 
           [0015]      FIG. 7B  shows the requirements for each software component that can be installed, according to an exemplary embodiment of the present invention. 
           [0016]      FIG. 8  shows the data structure that shows the maximum available capacity of each component when it is installed on a node for the first time, according to an exemplary embodiment of the present invention. 
           [0017]      FIG. 9  shows the installed software stack and available capacities for each component stored in the deployment repository, according to an exemplary embodiment of the present invention. 
       
    
    
     DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS 
       [0018]    Hereinafter, exemplary embodiments of the present invention will be described with reference to the accompanying drawings. It is to be understood that exemplary embodiments of the present invention described herein may be implemented in various forms of hardware, software, firmware, special purpose processors, or a combination thereof. An exemplary embodiment of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment containing both hardware and software elements. An exemplary embodiment may be implemented in software as an application program tangibly embodied on one or more program storage devices, such as for example, computer hard disk drives, CD-ROM (compact disk-read only memory) drives and removable media such as CDs, DVDs (digital versatile discs or digital video discs), Universal Serial Bus (USB) drives, floppy disks, diskettes and tapes, readable by a machine capable of executing the program of instructions, such as a computer. The application program may be uploaded to, and executed by, an instruction execution system, apparatus or device comprising any suitable architecture. It is to be further understood that since exemplary embodiments of the present invention depicted in the accompanying drawing figures may be implemented in software, the actual connections between the system components (or the flow of the process steps) may differ depending upon the manner in which the application is programmed. 
         [0019]    As used herein, the phrase “computing resource” generally refers to an entity that provides compute cycles for executing software instructions. Further, as used herein, “resources” generally refer to different entities that represent hardware, software, network, disk capabilities, etc., for example, as may be required by a composite business (enterprise) solution (or CBS as explained below). That is, in illustrative terms of embodiments described below, a resource can be defined as a container that provides a capability to host a service (i.e., a solution), and a computing resource would thus provide compute capability to host the service (solution). 
         [0020]    Furthermore, as used herein, a “software component” refers to a constituent of a solution that requires some capacity from the container hosting it. A deployed instance of a component consumes capacity from its container and in turn can acts as a container for one or more other components. A “hardware component” refers to a physical resource contributing to capacity of a computer system. As used herein, a “target” for a component would be the container in which it is hosted. 
         [0021]    It is to be appreciated that in an illustrative real world application of principles of the invention, resource allocations determined thereby may be utilized in data centers. For example, when an application for a customer needs to be hosted at a data center, the system administrator needs to identify servers that are capable of hosting the software components of the application. If a system administrator allocates new (previously undeployed) hardware for the application, then no resource allocation needs to be done. However, a downside of this approach is that hosting costs are high when the hardware is not shared. When the system administrator needs to identify hardware from currently deployed hardware resources, then resource allocation techniques of the invention would help the system administrator to identify hardware that meets the requirements of the software application. This results in lower costs as the hardware and software is now shared across multiple customers. 
         [0022]    By way of further example, the following are real world applications in which principles of the invention can be applied. 
         [0023]    IBM Lotus Connections is a collaboration solution which contains multiple independent components like “Blogs,” “Profiles,” “Activities,” “Dogears” and “Communities.” These components in turn depend on services provided by other software containers like “Application Server,” “Database Server,” “Directory Server,” “Web Server.” Each of these containers have their specific attributes to define capacities, e.g., a Directory Server can define capacity in terms of number of user/group entries and their level of detail and/or the number and kind of queries per time interval it can support. Still further, a Web 2.0 Mashup application combines the services provided by two or more independent component services as an integrated service. An enterprise mashup application which combines the enterprise employee organizational information with a location/map service to provide an organizational connectivity service is an example. 
         [0024]      FIG. 1  depicts a pictorial representation of a network data processing system, which may be used to implement an exemplary embodiment of the present invention. Network data processing system  100  includes a network of computers, which can be implemented using any suitable computers. Network data processing system  100  may include, for example, a personal computer, workstation or mainframe. Network data processing system  100  may employ a client-server network architecture in which each computer or process on the network is either a client or a server. 
         [0025]    Network data processing system  100  includes a network  102 , which is a medium used to provide communications links between various devices and computers within network data processing system  100 . Network  102  may include a variety of connections such as wires, wireless communication links, fiber optic cables, connections made through telephone and/or other communication links. 
         [0026]    A variety of servers, clients and other devices may connect to network  102 . For example, a server  104  and a server  106  may be connected to network  102 , along with a storage unit  108  and clients  110 ,  112  and  114 , as shown in  FIG. 1 . Storage unit  108  may include various types of storage media, such as for example, computer hard disk drives, CD-ROM drives and/or removable media such as CDs, DVDs, USB drives, floppy disks, diskettes and/or tapes. Clients  110 ,  112  and  114  may be, for example, personal computers and/or network computers. 
         [0027]    Client  110  may be a personal computer. Client  110  may comprise a system unit that includes a processing unit and a memory device, a video display terminal, a keyboard, storage devices, such as floppy drives and other types of permanent or removable storage media, and a pointing device such as a mouse. Additional input devices may be included with client  110 , such as for example, a joystick, touchpad, touchscreen, trackball, microphone, and the like. 
         [0028]    Clients  110 ,  112  and  114  may be clients to server  104 , for example. Server  104  may provide data, such as boot files, operating system images, and applications to clients  110 ,  112  and  114 . Network data processing system  100  may include other devices not shown. 
         [0029]    Network data processing system  100  may comprise the Internet with network  102  representing a worldwide collection of networks and gateways that use the Transmission Control Protocol/Internet Protocol (TCP/IP) suite of protocols to communicate with one another. The Internet includes a backbone of high-speed data communication lines between major nodes or host computers consisting of a multitude of commercial, governmental, educational and other computer systems that route data and messages. 
         [0030]    Network data processing system  100  may be implemented as any suitable type of networks, such as for example, an intranet, a local area network (LAN) and/or a wide area network (WAN). The pictorial representation of network data processing elements in  FIG. 1  is intended as an example, and not as an architectural limitation for embodiments of the present invention. 
         [0031]      FIG. 2  is a block diagram of a data processing system, which may be used to implement an exemplary embodiment of the present invention. Data processing system  200  is an example of a computer, such as server  104  or client  110  of  FIG. 1 , in which computer usable code or instructions implementing processes of embodiments of the present invention may be located. 
         [0032]    In the depicted example, data processing system  200  employs a hub architecture including a north bridge and memory controller hub (NB/MCH)  202  and a south bridge and input/output (I/O) controller hub (SB/ICH)  204 . Processing unit  206  that includes one or more processors, main memory  208 , and graphics processor  210  are coupled to the north bridge and memory controller hub  202 . Graphics processor  210  may be coupled to the NB/MCH  202  through an accelerated graphics port (AGP). Data processing system  200  may be, for example, a symmetric multiprocessor (SMP) system including a plurality of processors in processing unit  206 . Data processing system  200  may be a single processor system. 
         [0033]    In the depicted example, local area network (LAN) adapter  212  is coupled to south bridge and I/O controller hub  204 . Audio adapter  216 , keyboard and mouse adapter  220 , modem  222 , read only memory (ROM)  224 , universal serial bus (USB) ports and other communications ports  232 , and PCI/PCIe (PCI Express) devices  234  are coupled to south bridge and I/O controller hub  204  through bus  238 , and hard disk drive (HDD)  226  and CD-ROM drive  230  are coupled to south bridge and I/O controller hub  204  through bus  240 . 
         [0034]    Examples of PCI/PCIe devices include Ethernet adapters, add-in cards, and PC cards for notebook computers. In general, PCI uses a card bus controller while PCIe does not. ROM  224  may be, for example, a flash binary input/output system (BIOS). Hard disk drive  226  and CD-ROM drive  230  may use, for example, an integrated drive electronics (IDE) or serial advanced technology attachment (SATA) interface. A super I/O (SIO) device  236  may be coupled to south bridge and I/O controller hub  204 . 
         [0035]    An operating system, which may run on processing unit  206 , coordinates and provides control of various components within data processing system  200 . For example, the operating system may be a commercially available operating system such as Microsoft® Windows® XP (Microsoft and Windows are trademarks or registered trademarks of Microsoft Corporation in the United States, other countries, or both). An object-oriented programming system, such as the Java™ programming system, may run in conjunction with the operating system and provides calls to the operating system from Java programs or applications executing on data processing system  200  (Java and all Java-based marks are trademarks or registered trademarks of Sun Microsystems, Inc. in the United States, other countries, or both). 
         [0036]    Instructions for the operating system, object-oriented programming system, applications and/or programs of instructions are located on storage devices, such as for example, hard disk drive  226 , and may be loaded into main memory  208  for execution by processing unit  206 . Processes of exemplary embodiments of the present invention may be performed by processing unit  206  using computer usable program code, which may be located in a memory, such as for example, main memory  208 , read only memory  224  or in one or more peripheral devices. 
         [0037]    It will be appreciated that the hardware depicted in  FIGS. 1 and 2  may vary depending on the implementation. Other internal hardware or peripheral devices, such as flash memory, equivalent non-volatile memory, or optical disk drives and the like, may be used in addition to or in place of the depicted hardware. Processes of embodiments of the present invention may be applied to a multiprocessor data processing system. 
         [0038]    Data processing system  200  may take various forms. For example, data processing system  200  may be a tablet computer, laptop computer, or telephone device. Data processing system  200  may be, for example, a personal digital assistant (PDA), which may be configured with flash memory to provide non-volatile memory for storing operating system files and/or user-generated data. A bus system within data processing system  200  may include one or more buses, such as a system bus, an I/O bus and PCI bus. It is to be understood that the bus system may be implemented using any type of communications fabric or architecture that provides for a transfer of data between different components or devices coupled to the fabric or architecture. A communications unit may include one or more devices used to transmit and receive data, such as modem  222  or network adapter  212 . A memory may be, for example, main memory  208 , ROM  224  or a cache such as found in north bridge and memory controller hub  202 . A processing unit  206  may include one or more processors or CPUs. 
         [0039]    Methods for automated provisioning according to exemplary embodiments of the present invention may be performed in a data processing system such as data processing system  100  shown in  FIG. 1  or data processing system  200  shown in  FIG. 2 . 
         [0040]    It is to be understood that a program storage device can be any medium that can contain, store, or be used to transport a program of instructions for use by or in connection with an instruction execution system, apparatus or device. The medium can be, for example, an electronic, magnetic, optical, or semiconductor system (or apparatus or device) or a propagation medium. Examples of a program storage device include a semiconductor or solid state memory, magnetic tape, removable computer diskettes, RAM (random access memory), ROM (read-only memory), rigid magnetic disks, and optical disks such as a CD-ROM, CD-R/W and DVD. 
         [0041]    A data processing system suitable for storing and/or executing a program of instructions may include one or more processors coupled directly or indirectly to memory elements through a system bus. The memory elements can include local memory employed during actual execution of the program code, bulk storage, and cache memories that provide temporary storage of at least some program code to reduce the number of times code must be retrieved from bulk storage during execution. 
         [0042]    Data processing system  200  may include input/output (I/O) devices, such as for example, keyboards, displays and pointing devices, which can be coupled to the system either directly or through intervening I/O controllers. Network adapters may also be coupled to the system to enable the data processing system to become coupled to other data processing systems or remote printers or storage devices through intervening private or public networks. Network adapters include, but are not limited to, modems, cable modem and Ethernet cards. 
         [0043]      FIG. 3  depicts a schematic representation of a service delivery environment, which may be used to implement an exemplary embodiment of the present invention. Referring to  FIG. 3 , service delivery environment  300  includes a farm of physical servers  302 , DMZ (demilitarized zone)  306  and management servers  312 . The term “demilitarized zone” or acronym “DMZ” refers to a network area that sits between an organization&#39;s internal network and an external network, such as the Internet. 
         [0044]    User requests from the Internet or an intranet are received by a router device. For example, a router device may be located within the DMZ  306 . The router device may be implemented by a reverse proxy, such as IBM&#39;s WebSeal product. 
         [0045]    User requests may be directed via network  308  to a provisioning solution that is hosted on a collection of real (physical) or virtual machines  310  running on the server farm  302 . Management servers  312  that may be used to manage the server farm  302  are coupled via network  308  to the physical servers  302 . The management servers  312  may be used by system administrators  304  to manage and monitor the server farm. Software running on the management servers  312  may assist with various tasks such as software metering, application provisioning, monitoring all (or selected) applications, and problem determination of the server farm. 
         [0046]      FIG. 4  depicts an example of a logical application structure containing a resource dependency characterization of a sample application, according to an exemplary embodiment of the present invention. Referring to  FIG. 4 , the example logical application structure is a dependency graph containing resource dependency characteristics of the sample application. However, it is to be understood that any suitable logical application structure may be employed. 
         [0047]    A dependency graph may be expressed as an eXtensible Markup Language (XML) file that highlights the relationships and dependencies between different components. In the example depicted in  FIG. 4 , the “Loan Solution”  422  largely depends on the availability of three components, WebSphere Portal Server  424 , WebSphere Process Server  430  and DB 2  server  434 . The WebSphere Portal Server  424  depends on the availability of WebSphere Application Server  426  and DB 2  client  428 . The WebSphere Process Server depends upon DB 2  client  432  and WebSphere Application Server  436 . 
         [0048]      FIG. 5  shows the logical architecture of a placement controller component. The architecture consists of a solution repository ( 504 ) and a deployment repository ( 506 ). The solution repository contains metadata and dependency graphs for each composite enterprise solution. The metadata comprises required capacity needs of each software components in the solution dependency graph. The deployment repository comprises mappings of software components deployed to physical resources, along with total available capacity associated with each resource. Also shown is provisioning manager  508 , discussed below. 
         [0049]      FIG. 6  shows the steps that the placement controller takes to determine the mapping of a composite business (enterprise) solution (CBS) to a set of computing resources in a distributed environment. In step  602 , the placement controller takes in as input the name of the CBS. In step  604 , the placement controller retrieves the dependency graph for the CBS from the solution repository. The dependency graph is stored as part of the CBS metadata in the solution repository. The placement controller generates a post order traversal of the dependency graph in step  606 . Using the information in the deployment repository, the placement controller retrieves the specification for a set of candidate targets for the CBS. The specification is a representation of available capacities for each software and hardware component available on a specific target. 
         [0050]    In step  608 , the placement controller iterates through all the components in the post order representation of the dependency graph, and maps a component if the available capacity for that software component is more than the required capacity for the CBS component ( 612 ). In step  614 , the required capacity is subtracted from the available capacity of the software components. If enough capacity is not available the in step  620 , then the mappings of dependent components is dropped and the target is removed from consideration for this CBS component. In step  616 , the algorithm completes with the recommended mapping when all the CBS components are mapped to valid targets. It is to be appreciated that the term “valid” generally refers to the condition that the identified targets meet and satisfy the requirements (i.e., capacity, CPU, etc.) of the CBS components. 
         [0051]      FIG. 7A  shows the metadata data structure associated with each solution stored in the solution repository ( 702 ). The metadata represents the requirements for installing an instance of the solution component. 
         [0052]      FIG. 7B  shows the requirements for each software component that can be installed. Each data structure (table  704 ,  706 ,  708 ,  710  and  712 ) represents the dependency of each component on other components. 
         [0053]      FIG. 8  shows the data structures (tables  802 ,  804 ,  806 ,  808 ,  810  and  812 ) that show the maximum available capacity of each component when it is installed on a node for the first time. These data structures are stored in the deployment repository. The placement controller subtracts required capacity from the maximum available capacity each time a software component is mapped to a resource. 
         [0054]    In accordance with tables  902 ,  904 ,  906  and  908 ,  FIG. 9  shows the installed software stack and available capacities for each component stored in the deployment repository. As an example, we map the composite application of  FIG. 4  using the steps outlined in  FIG. 6 . The post order traversal of the dependency graph yield sequence ACBDEFG, where letters A through G represent the nodes in the dependency graph of  FIG. 4 . The resource pool has four servers: S 1 , S 2 , S 3 , and S 4 . The algorithm identifies starts with the first node in the postorder traversal and maps A to server S 1  as it meets the requirements of A. Using a similar logic, the algorithm also maps node C to server S 1 . Since the dependency and available capacity requirements of node B are satisfied, the algorithm maps node B to server S 1 . Having mapped nodes A, C, and B to server S 1 , the placement controller decrements the available capacity for server S 1  by the sum total of requirements of node A, C, and B. Next, the placement controller considers node D, and narrows the target resources to S 1 , S 2 , S 3  as all have adequate capacities available to meet the requirements. For example, if the placement controller selects S 1  for node D, it would fail to map node E on S 1  as there is no sufficient capacity available on server S 1  to satisfy the needs of WebSphere App Server. The algorithm would then remap nodes D and E to server S 2 , and node F to server S 2 . Lastly, node G is mapped to S 3  as it has the DB 2  Server installed and sufficient capacity is available to host the DB 2  server. Now that all the nodes are mapped to resources, the placement controller completes the steps. Any software components that are not installed on target resources are automatically installed by the provisioning manager based on the recommended mappings. 
         [0055]    Although illustrative embodiments of the present invention have been described herein with reference to the accompanying drawings, it is to be understood that the invention is not limited to those precise embodiments, and that various other changes and modifications may be made by one skilled in the art without departing from the scope or spirit of the invention.