Abstract:
A distributed hash table infrastructure is described that supports pluggable modules for various services. Transport providers, security providers, and other service providers may be swapped, providing flexibility in supporting various devices and networking configurations.

Description:
BACKGROUND 
       [0001]    A hash table defines a mapping relationship between keys and their associated values. A Distributed Hash Table (DHT) implements the functionality of a hash table in a distributed fashion, providing a remote lookup service from any participating node in the DHT to retrieve the value associated with a given key. DHTs are used to provide services, including distributed file systems, peer-to-peer file sharing, cooperative web caching, multicast, domain name services, and instant messaging, for example. 
         [0002]    DHT can implement large-scale resource indexing and discovery services, as well as distributed file systems. An application example is to use DHT in a distributed content lookup and retrieval system to store the network addresses of contents, indexed by the hash of the contents. Or the DHT can be used to store the contents directly, depending on the implementation. 
         [0003]    DHT is the foundation of many Peer-to-peer network applications that emphasize the characteristics of decentralization, scalability, and fault tolerance. The semantic-free nature of the key-value mappings allows applications on top of DHT to define arbitrary relationship between keys (index) and values (data). It also decouples the actual locations from any existing structure of the contents and services. This property makes it possible to achieve load-balancing and avoid centralization even for services with hierarchical architecture. 
       SUMMARY 
       [0004]    The following presents a simplified summary of the disclosure in order to provide a basic understanding to the reader. This summary is not an extensive overview of the disclosure and it does not identify key/critical elements of the invention or delineate the scope of the invention. Its sole purpose is to present some concepts disclosed herein in a simplified form as a prelude to the more detailed description that is presented later. 
         [0005]    In accordance with one implementation presented herein, a distributed hash table may be used to store in a distributed manner identified by numeric keys, with application-configurable (pluggable) modules, such as bootstrapping mechanisms, transports, storage or secure routing protocol mechanisms. This allows, for example, a hash table to be distributed across disparate nodes, allowing each node to have appropriate security and transport modules for its own operating environment. Distributed hash tables may be built using the Distributed Routing Tables (DRT) key-based routing infrastructure, which identifies the node which manages the storage of a data item based on its key. 
         [0006]    Nodes may exist on various types of devices by providing techniques to permit “plugging in” appropriate service providers, such as security or storage modules for each device. For example, on some devices, it may be desired to store hash table key-value pairs in memory, while on other devices, on-disk may be a preferred format. For another example, a security module for a handheld computer may differ from one for a server. 
         [0007]    Many of the attendant features will be more readily appreciated as the same becomes better understood by reference to the following detailed description considered in connection with the accompanying drawings. 
     
    
     
       DESCRIPTION OF THE DRAWINGS 
         [0008]    The detailed description provided below in connection with the appended drawings is intended as a description of example implementations and is not intended to represent the only forms in which an application-configurable distributed hash table framework may be constructed or utilized. The description sets forth the functions of example implementations and the sequence of steps for constructing and operating the examples. However, the same or equivalent functions and sequences may be accomplished by alternate implementations. 
           [0009]    The present description will be better understood from the following detailed description read in light of the accompanying drawings, wherein: 
           [0010]      FIG. 1  is a block diagram of an example operating environment in which an application-configurable distributed hash table framework may be implemented. 
           [0011]      FIG. 2  is a block diagram providing additional detail for an example of an implementation of an application-configurable distributed hash table framework. 
           [0012]      FIG. 3  shows an example flow diagram between nodes in an application-configurable distributed hash table. 
           [0013]      FIG. 6  illustrates a component diagram of a computing device for implementing one or more embodiments. 
       
    
    
     DETAILED DESCRIPTION 
       [0014]    Described herein are, among other things, examples of various technologies and techniques that allow an application-configurable distributed hash table framework. Although the examples are described and illustrated herein as being implemented in a personal computer system, the system described is provided as an example and not a limitation. As those skilled in the art will appreciate, the present examples are suitable for application in a variety of different types of systems. 
         [0015]    In the figures, like reference numerals are used throughout several drawings to refer to similar components. 
         [0016]    A hash table defines a mapping relationship between keys and their associated values. A DHT implements the hash table functionality in a distributed fashion, providing a remote lookup service from any participating node in the DHT to retrieve the value associated with a given key.  FIG. 1  shows an example of a conceptual system architecture diagram  100  of a DHT. A DHT consists of a set of nodes; each stores a part of the overall hash table, and a forwarding table (not shown) of other nodes to find the remaining part of the hash table. The forwarding tables collectively determine the topology (also called a mesh or overlay) of the DHT, and in this example is a form of Key-Based Routing (KBR) as opposed to the traditional address-based routing in the Internet. In this example, the contents of hash table  100  are shown, with keys and values. Distributed hash table  105  is distributed across  510 ,  4510 ,  10010 , and  25010  stored on nodes  500 ,  4500 ,  10000 , and  25000  respectively. In this example, the distribution is implemented on distributed routing table  110  and is based on node IDs, so that the key/value pairs are each stored on the node id closest numerically to the key. Keys  950  and  1100  are stored with their corresponding values on the node with ID  500  because they are numerically closer to  500  than to  4500 , 10000 , or  25000 . In other implementations, other techniques for determining which node would store each key/value pair may be used. One skilled in the art will recognize that IP address, MAC address, geographical location, user name, or any number or combination of different factors may be used. 
         [0017]    The management interface of a DHT allows users and applications to insert or delete nodes, and to update the table by adding, removing, or changing the key-value pairs. Any operation on a record in the DHT can be divided into two phases. The first phase is to locate the root node of the key value through the underlying Key-Based Routing or the overlay protocol, DRT in this example. After the root node is found, the second phase is to contact the root node of the record to perform the designated operation on the record. The root node lookup operation is performed within the DRT. 
         [0018]    The querying node (the initiator) will consult its own DRT forwarding table, obtain the next closest node to a given key, and send the root node query to the next node. The next node will in turn look up its own DRT forwarding table, and reply the query with the next closest node in the key space to the key of the query. The initiator then repeats the querying process iteratively until the root node of the key is reached. This lookup process can also be done recursively where each intermediate node queries its next closest node before replying, or in a hop-by-hop fashion where each intermediate node forwards the query to the next closet node. The specifics of the lookup operations depend on the overlay technology. 
         [0019]      FIG. 2  is a block diagram providing additional detail for an example of an implementation of an application-configurable distributed hash table framework. 
         [0020]    Applications  200  communicate with DHT  100  via an application programming interface (API)  210 . API  210  provides the interface to add, get, or remove data from DHT  100 . DHT core processing  260  provides the functionality, using various components such as migration  220 , replication  230 , security provider  240 , transport  250 , record processing and storage  270 , bootstrap  280 , and a key-based routing provider  205 . Each of these components rely on other components; transport  250  uses Winsock  201 , security provider  240  interacts with KBR security provider  203 , and bootstrap  280  depends on KBR bootstrap  207 . 
         [0021]    In this example, certain components are configurable (pluggable) by a management application. This DHT  100  will provide a pluggable interface to storage provider  270  that provides the hash table key and value data storage. A pluggable security module  240  (providers/protocols) for the DHT is also provided for. Other core components include bootstrap  280  and migration mechanisms  220  to handle node join and leave, a (tunable) replication policy module  220  to increase fault tolerance at the DHT layer, and provisioning for record integrity protection. Each of these components is pluggable, allowing for the most appropriate technology for the specific node, the nature of the DHT, or any other relevant factors. 
         [0022]    Transport provider  250  implements a message transport service for DHT and determines the transport protocol used in communication between DHT nodes. By way of example, but not limitation, transport providers include TCP or UDP over IPv6, HTTP- or RPC-based transports. One skilled in the art will recognize that other types of transport provider may be used as well. The applications, services, or system administrators using the DHT may provision the IPsec or firewall policies if required. The security in transport provider  250  may be independent from the Security provider of the DHT. Transport provider  250  is a pluggable component in the DHT architecture, and may be replaced by another transport provider with different features. 
         [0023]    Replication module  230  is used to provide copies of key-value pairs across multiple nodes. A root node in DHT can replicate its local hash records to a set of nodes for both backup and performance enhancement such that one of the neighboring nodes can answer for the root node if necessary. The set of close neighboring nodes is usually the leaf set of the root node, but can also be defined by some other metrics such as the closest N number of nodes, if the underlying routing system does not support the notion of leaf set. Although the leaf set selection policy for replication will affect the resulting traffic needed to move and synchronize the data and degree of reliability measure. 
         [0024]    Security provider  240  authenticates and authorizes whether a node can join an existing DHT, and whether it can perform DHT operations on the records stored in the DHT. For example, security provider  240  may restrict operations that may be performed on the DHT, such as looking up or storing data. Security provider  240  may optionally authenticate and/or encrypt the content (value or data portion of a record) to provide integrity and confidentiality services. Examples of security provider functionality include some forms of password authentication, PKI-based certificate authentication, etc. Security provider  240  and the corresponding security credentials (e.g., passwords, certificates, etc.) of the DHT are provisioned by the application  200 , and will be used in both the DHT and DRT. 
         [0025]    Record processing and storage module  270  defines the operational semantics for processing and storing DHT records. It also allocates and manages record storage for the local hash table. Record processing and storage provider  270  is a pluggable module in the design. The pluggable nature of the various modules is illustrated in  FIG. 3 . 
         [0026]      FIG. 3  shows an example DHT  300 , with a transport provider module  250 . Various situations may make it useful to replace transport provider module  250  with transport provider module  350 , such as a change in network configuration, a desire to improve compatibility with additional devices, or any number of other conditions. In this example, a call has been received by API  210 , with a request that the transport provider module  350  be used. As a result, transport provider module  250  is removed and module  350  replaces it. 
         [0027]      FIG. 4  shows a DHT  305 , which is similar to DHT  300  except that Transport provider module  250  has been replaced by transport provider module  350 , showing completion of the steps begun in  FIG. 3 . 
         [0028]      FIG. 5  shows an example data flow between the applications  200  from  FIG. 2 , the DHT on the client side node  500 , and the record processing and storage  270  at the root node DHT  10000  in example DHT detail  500 . In this example, application  200  passes commands, such as GET, PUT, or REMOVE to DHT  510 . The key associated with the command is found in DHT  10010  on Node ID  10000 . DHT  510  passes the command to DHT  10010 , where processing and storage module  270  implements simple hash table semantics, with each record entry being a (Key, Value) tuple. The DHT maintains the mapping relationship between the keys to their corresponding values. Subsequent updates (PUT) to the same key result in overwriting the value. Complex semantics, such as mapping each key to a list (or set) of values can be implemented by plugging in a custom processing and storage module. The processing and storage module  270  may determine whether the local hash table is stored in system memory, local file systems, or remote file systems. 
         [0029]      FIG. 6  illustrates a component diagram of a computing device according to one embodiment. The computing device  600  can be utilized to implement one or more computing devices, computer processes, or software modules described herein. In one example, the computing device  600  can be utilized to process calculations, execute instructions, receive and transmit digital signals. In another example, the computing device  600  can be utilized to process calculations, execute instructions, receive and transmit digital signals, receive and transmit search queries, and hypertext, compile computer code, as required by the consumer computing device  106 , the merchant computing device  108 , the merchant computing device  114 , the listing web service  202 , the web server  204 , and the search engine  206 . 
         [0030]    The computing device  600  can be any general or special purpose computer now known or to become known capable of performing the steps and/or performing the functions described herein, either in software, hardware, firmware, or a combination thereof. 
         [0031]    In its most basic configuration, computing device  600  typically includes at least one central processing unit (CPU)  602  and memory  604 . Depending on the exact configuration and type of computing device, memory  604  may be volatile (such as RAM), non-volatile (such as ROM, flash memory, etc.) or some combination of the two. Additionally, computing device  600  may also have additional features/functionality. For example, computing device  600  may include multiple CPU&#39;s. The described methods may be executed in any manner by any processing unit in computing device  600 . For example, the described process may be executed by both multiple CPU&#39;s in parallel. 
         [0032]    Computing device  600  may also include additional storage (removable and/or non-removable) including, but not limited to, magnetic or optical disks or tape. Such additional storage is illustrated in  FIG. 6  by storage  206 . Computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data. Memory  604  and storage  606  are all examples of computer storage media. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by computing device  600 . Any such computer storage media may be part of computing device  600 . 
         [0033]    Computing device  600  may also contain communications device(s)  612  that allow the device to communicate with other devices. Communications device(s)  612  is an example of communication media. Communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media. The term “modulated data signal” means a signal that has one or more of its characteristics set or changed in such a manner as to encode information in the signal. By way of example, and not limitation, communication media includes wired media such as a wired network or direct-wired connection, and wireless media such as acoustic, RF, infrared and other wireless media. The term computer-readable media as used herein includes both computer storage media and communication media. The described methods may be encoded in any computer-readable media in any form, such as data, computer-executable instructions, and the like. 
         [0034]    Computing device  600  may also have input device(s)  610  such as keyboard, mouse, pen, voice input device, touch input device, etc. Output device(s)  608  such as a display, speakers, printer, etc. may also be included. All these devices are well known in the art and need not be discussed at length. 
         [0035]    Those skilled in the art will realize that storage devices utilized to store program instructions can be distributed across a network. For example, a remote computer may store an example of the process described as software. A local or terminal computer may access the remote computer and download a part or all of the software to run the program. Alternatively, the local computer may download pieces of the software as needed, or execute some software instructions at the local terminal and some at the remote computer (or computer network). Those skilled in the art will also realize that by utilizing conventional techniques known to those skilled in the art that all, or a portion of the software instructions may be carried out by a dedicated circuit, such as a DSP, programmable logic array, or the like.