Patent Application: US-91803201-A

Abstract:
the present invention is a system and method for distributed , highly scalable , wide area peer - to - peer network data storage . the functionally equivalent servers in the system are divided into groups . each server maintains a dynamic list which is polled to determine the availability of the closest neighbor servers . each server is switched between the groups of servers to optimize network connectivity parameters . data and directory files are divided into a plurality of pieces which are stored on different servers . files are uniformly and independently named , utilizing a tree with a common root , logical pathways , and unique file identifiers . when a server receives a client request for file system access , the plurality of file pieces are collected and sent to the client server from the neighbor servers simultaneously in order to optimize bandwidth . servers with maximum throughput capacity are utilized for highest transmission speed and reduced processing time .

Description:
the use of the term “ peer - to - peer network ”, means that the world wide web ( internet ) is involved in this invention . specifically , all the servers supporting the www - type services have the name that can be written with the help of a url system ( uniform resource locator ). actually , the url is the address in the peer - to - peer server network . the client that works with the service using the url usually connects with one separated server and receives all the data from the separated server . the uniformity of name space is guaranteed because the client &# 39 ; s access via url doesn &# 39 ; t depend on the client and is unique for each resource . the storage operates on file level , i . e ., the information storage unit the client works with is a file . to provide fault - tolerance , it is suggested that any file to be stored should be divided into pieces in a way that makes it possible to restore the file from the pieces . the number of pieces can be more than necessary for the restoration of one file . additionally , the pieces must be functionally equivalent such that it is necessary to collect only an exact number of pieces in order to properly restore the file . to illustrate the present invention , consider a system where the storage is organized by placing every piece of the stored file on a separate server . when implementing a system where every piece of the stored file is on a separate server , switching off some servers does not block access to data because the number of file pieces exceeds what is necessary to reconstruct the file . therefore , the necessary file pieces can be easily found to restore the file . the absence of a unique piece among the pieces guarantees that where a server cannot be accessed , the file can still be reassembled . consider a system where there is some performance characteristic associated with the network where the servers are located . this performance characteristic shows the “ network distance ” from one server to another . for example , such a performance characteristic can be server - to - server response time or the real channel performance between servers . of course , these performance characteristics can vary over time . nevertheless , changes in performance characteristics over time are usually not significant . more particularly , the “ network distance ” generally does not change . thus , one can define the distance between the servers . the servers are organized into groups such that the distance between any two of the servers does not exceed the fixed limit according to the performance characteristics . the size of the group of servers should not be very big , typically 5 - 10 servers as shown in fig1 . assume that the group of servers overlap ; i . e ., the same server can be part of several groups . it is clear that the transitivity relationship between servers isn &# 39 ; t developed : if servers c 1 and c 2 are in the first group and servers c 2 and c 3 are in the second group , then correlations d ( c 1 , c 2 ) less than or equal to l and d ( c 2 , c 3 ) ) less than or equal to l are developed ; and correlation d ( c 1 , c 3 ) less than or equal to l is clearly not developed . here , d ( a , b ) is the distance between the servers a and b and l is the distance limit . for clarity , a server belonging to two groups ( like c 2 ) is called a boundary server ( see fig2 ). assume further that any group has at least one server that is part of another group and that all groups are connected . therefore , a path exists from any group to any other group via a set of boundary servers ( see fig1 — the solid lines connect servers via boundary servers ). the scalability and fault - tolerance of the foregoing system is defined by many factors , especially by the algorithms defining the work stored on all of the servers . all the algorithms acting in the topology of such links of the servers must be of a local character , i . e ., there shouldn &# 39 ; t be any places in the system where there is a full list of the servers . the same thing can be said about the system for naming the resources : there shouldn &# 39 ; t be a single place in the system that could “ disturb ” the name uniqueness , typically with respect to catalog maintenance . this makes it possible for the system to grow and self - organize , especially when starting new servers in the internet - like network . the addition of new servers and switching off of old ones influences only their closest neighbors and does not depend upon network size . thus , each server keeps a dynamic list of neighbor servers . this list changes over time , and the list is significantly smaller than the complete list of all the servers in a system . the evolution of the group of servers over time consists of two main stages in their functioning : the process of adding and deleting new servers and grouping system reconstruction process . the last process occurs when changing the terms of network existence and the corresponding performance characteristic (“ distance ”) between the servers . when adding a new server , the new server must be put into the group where the limit on distance threshold between servers will be implemented with all the servers in the group . to provide the correct arrangement of servers , the algorithm connects the new server to the first group of servers ( that comes in the way ) and later a decision iterative improvement is used . as shown in fig3 this means that , at first , the new server n connects to an existing group ( group 3 ) and gets the list of the servers that also belong to other groups ( boundary servers ). next , the new server gets the list of the group &# 39 ; s members from each server and measures the “ distance ” between servers . thus , the “ distance ” between group members is determined . the average distance is then calculated for every group and the minimal average distance is chosen . if this minimal average distance compares to the group to which the server belongs , then no actions are taken and it is considered that the server is already in the optimal group . as shown in fig4 if the minimal average distance does not compare , the new server n switches off from the current group ( group 3 ) and reconnects to the server group with the minimal average “ distance ” ( group 2 ). then the operation is repeated for all the neighbor groups . thus , as shown in fig5 eventually , the server n is connected to the group ( group 1 ) where the distance parameter of the links with the neighbor is optimal . when a server disconnects from the system , all members of all of the groups where the separated server is located must delete that server from the list of the group &# 39 ; s members . this can be done automatically via a periodic , prompt notification process which indicates whether the server is operational and accessible . the second process in the system is the “ distance ” changing over time . the need for this process can be the changing of the load parameters of a channel between the servers . for example , this changing is needed because of the changing number of clients at the start or finish of the working day and the corresponding change in the number of clients using the internet channel . thus , the same procedure is necessary as that described in the algorithm for the addition of a new server . the server receives the list of all of the servers in the group that also belong to other groups , i . e ., boundary servers . then from each server it also gets the group member list and then measures the “ distance ” to each server . thus , the “ distance ” to all group members can be determined . average distance is calculated for every neighbor group , and among the averaged distances the minimal distance is chosen . if the average distance is comparable to that of the group the server belongs to , no actions are taken and the server is deemed to be in the optimal group . if the average distance does not compare , the new server disconnects from the group and connects to a group where the average “ distance ” is less . the operation is then repeated for all the neighbor groups . thus , eventually , the server is connected to the group where the distance parameters of the links with the neighbor is optimal . the use of such grouping algorithms which are oriented to only local work with direct neighbor servers , allows optimal server arrangement for the chosen network performance characteristic . using such connections , the response time can be optimized between servers , assuming that connection uses the chosen links between the servers . thus the support of a connected network of the servers that are organized into local groups to achieve the optimal connection between servers from the point of view of an input network metric is completed . such a server network is used to organize the data storage . to access data storage , the client can connect to any server belonging to the network , as all of them are functionally identical and the file availability doesn &# 39 ; t depend on the server chosen for connection . the algorithm of the selection of server connection is the same as the algorithm of the new server connection to the network . initially , the client connects to any group of servers and then gets the list of the group &# 39 ; s servers identifying those which belong to another group , i . e ., boundary servers . then , from every server the client gets the list of neighbor group servers and measures the “ distance ” to every server on the metric . thus , the “ distance ” to all the members of the groups that are neighbors to which the chosen server belongs is determined . from all the “ distance ” figures , the minimal distance is chosen . if the chosen server belongs to the group to which the client has already connected , then no actions are taken and it is considered that the client has been optimized . if not , then the client disconnects and reconnects to the server to which the “ distance ” is the minimal one . then the operation is repeated for all the neighbor groups . thus , eventually , the client is connected to the server where the distance parameters of the connection to the server is optimal ( see fig6 ). as mentioned above , it is necessary to repeat the procedure described in the previous algorithm periodically ( usually in one hour intervals depending on the internet state ). the client gets the list of all servers in the current group , marking those that belong to several groups , i . e ., boundary servers . then the client gets the list of neighbor group members form the boundary servers and measures the “ distance ” to each of the boundary servers on the metric . thus , the “ distance ” to the members of all neighbor groups is determined among all the distances . the minimal distance is then chosen . if the minimal distance value is the distance to the server to which the client has already been connected , then it is considered that the client has an optimal connection and no actions are performed . otherwise , the client disconnects from the current server and reconnects to the server having a lesser “ distance ” value . the same procedure is then repeated for the neighbors of the new group . thus , eventually the client is connected to the server with the optimal “ distance ” parameters . to implement the disclosed file storage system of connected servers , it is suggested that all files should be divided into two classes : common data files and directory files . for access to common files , there is a common name space for files . to access a particular file , the client specifies the file name and the path to the file from the root directory . the path does not depend either on client position in the internet or the current server to which the client is connected . the system of directory files defines the way the file requested by the client will be restored . the directory file transforms the logical name of the file requested into an identifier that is used to obtain file content . such procedure is to be performed for each subdirectory starting with the upper one . for example , to access the file having name “ c ” and the path “ aaa / bbb / c ”, the directory file is found from a list of the files in the root directory . then to choose the record corresponding to the file “ aaa ” from the list , we get information that “ aaa ” is the directory file itself . the procedure is repeated for the file “ bbb ” and finally , the file “ c ” is found ( see fig7 ). thus , the directory is the set of corresponding file records . every file record contains the logical file name and the unique file identifier . for the entire system , all files including the directory ones are the same ; each file has a unique file identifier which is used to reconstruct the file at the client level . for the directory file , the server itself can be considered a client if it asks for access to the directory as described above . the unique file identifier is generated when the file is created . its uniqueness is guaranteed with some probability by the local algorithms without a need for confirmation . to work with such a file storage system , the client connects to the server using the method described above and sends the request for the file operation , for example , to write a file record . to do so , the client divides the file into a set of pieces with the features mentioned above , and sends them to the server . then the server distributes these pieces among all of the servers of the group . then only the boundary servers of the group , in turn , send these pieces further until all of them are distributed between the servers ( it can be one or several pieces per server ). while the file is dividing into pieces , a unique identifier is generated for each of the pieces that later is used for identification . to read the file , the client connects to any of the system servers and sends the request with the file name . the server transforms the requested file name into a unique identifier , using the procedure mentioned above and collects the necessary number of the file pieces . at first , the server checks if these pieces are available on the server , if the number of pieces available is insufficient , the server then forwards the request to other group servers and then the boundary servers , in turn , to send the requests to the neighbors . thus , the server collects the necessary file pieces and sends them to the client . the client then restores the original file from the pieces . according to this scheme , data flows through the less utilized network channel , thus guaranteeing an optimal response time . moreover , as the server receives the requested file pieces from the neighbor servers in parallel mode , the pieces required to restore the file are collected much faster as compared to receipt of the pieces from a single server . thus , simultaneous use of several access channels results in optimal network loading . moreover , if the file pieces are requested by several neighbor servers simultaneously , the server that sends a piece faster will be sending more information . this is because when the first piece is received , the server is ready to send the second one . utilization of maximum throughput capability of the servers provides the highest speed and reduces the request processing time and network overloading . as a result of the client - server topology algorithm described above , client - server requests use optimal network traffic , which minimizes delays in request processing . the client is connected to the server with the highest throughput capacity . the disclosed system and method has been disclosed by reference to its preferred embodiment . those of ordinary skill in the art will understand that additional embodiments of the disclosed system and method are made possible by the foregoing disclosure . such additional embodiments shall fall within the scope and meaning of the appended claims . anderson , tom , et al . 1995 . serverless network file systems . 15th symposium on operating systems principles , acm transactions on computer systems . bach , maurice , 1987 . design of the unix operating system by marice j . bach , maurice bach . 1 edition ( feb . 27 , 1987 ) prentice hall ; isbn : 0132017997 . beheler , ann . data communications and networking fundamentals using novell netware ( 4 . 11 ) prentice hall / 1998 / 0135920078 . braam , p . j . 1998 . the coda distributed file system (# 74 ) linux journal , # 50 jun . 1998 . campbell , richard and campbell , andrew . 1997 . managing afs : the andrew file system . prentice hall 1 , isbn : 0138027293 . chet , brian pawlowski . 1994 . nfs version 3 design and implementation . usenix summer 1994 . crowley , charles 1997 operating systems : a design - oriented approach . irwin . 1997 . isbn 0 - 256 - 15151 - 2 . 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