Data encryption in a network memory architecture for providing data based on local accessibility

Information

  • Patent Grant
  • 10091172
  • Patent Number
    10,091,172
  • Date Filed
    Friday, May 6, 2016
    8 years ago
  • Date Issued
    Tuesday, October 2, 2018
    5 years ago
Abstract
A network memory system is disclosed. The network memory system comprises a first appliance configured to encrypt first data, and store the encrypted first data in a first memory device. The first appliance also determines whether the first data is available in a second appliance and transmits a store instruction comprising the first data based on the determination that the first data does not exist in the second appliance. The second appliance is configured to receive the store instruction from the first appliance comprising the first data, encrypt the first data, and store the encrypted first data in a second memory device. The second appliance is further configured to receive a retrieve instruction comprising a location indicator indicating where the encrypted first data is stored, process the retrieve instruction to obtain encrypted response data, and decrypt the encrypted response data.
Description
BACKGROUND
1. Technical Field

The present invention relates generally to maintaining the compliance of data in a network and more particularly to encrypting data in a network memory architecture.


2. Description of Related Art

To allow remote employees access to an enterprise's information systems, organizations typically choose between two networking approaches: centralized servers or distributed servers. Centralized server implementations have the advantage of simplicity since an information technology (IT) professional centrally manages, maintains, and enforces policies for the organization's data.


An issue that arises in allowing remote access to information is that unauthorized users may also gain access to the organization's data. Additionally, legislation in the United States and individual states requires that certain information is encrypted and/or make the organization civilly liable for injuries resulting from data breaches. Two examples of federal legislation requiring compliance include the Health Insurance Portability and Accountability Act (HIPAA) and the Sarbanes-Oxley Act. To secure the data and memory against theft, viruses, and hackers, the data is encrypted using an algorithm such as Advanced Encryption Scheme (AES), Data Encryption Scheme (DES), or Triple DES. However, two issues arise when encrypting data on a network. First, encryption can negatively affect performance. Second, when not encrypted, data is still vulnerable to unauthorized use.


Many organizations select the distributed server implementation to mitigate some of the problems with the centralized server implementation. FIG. 1 illustrates a distributed server system 100 in the prior art. The distributed server system 100 includes a branch office 110, a central office 120, and a communication network 130. The communication network 130 forms a wide area network (WAN) between the branch office 110 and the central office 120.


In the distributed server system 100, the branch servers 140 (e.g., email servers, file servers and databases) are placed locally in the branch office 110, rather than solely in the central office 120. The branch servers 140 typically store all or part of the organization's data. The branch servers 140 generally provide improved application performance and data access for the computers 160. The branch servers 140 respond to a request for the organization's data from the local data. For each request for the data, the central servers 170 potentially do not need to transfer the data over the communication network 130 (i.e., the WAN), via router 180 and router 150. Synchronization and backup procedures are implemented to maintain the coherency between the local data in the branch office 110 and the data in the central office 120.


Unfortunately, managing the distributed server system 100 is complex and costly. From a physical point of view, the distributed server system 100 with one hundred branch offices requires an order of one hundred times more equipment than a centralized server approach. Each piece of the equipment not only needs to be purchased, but also installed, managed, and repaired, driving significant life cycle costs. The branch office 110 may need additional local IT personnel to perform operations because of this “Server Sprawl”. Furthermore, the multiplication of managed devices means additional license costs, security vulnerabilities, and patching activities.


In distributed server implementations (e.g., the distributed server system 100), the data, including the “golden copy” or most up-to-date version of mission critical data, is often stored (at least temporarily) only on the branch servers 140 in the branch office 110. Organizations implement complex protocols and procedures for replication and synchronization to ensure that the mission critical data is backed up and kept in-sync across the WAN with the central servers 170.


Security vulnerabilities are a particular problem in providing compliance to the distributed server system 100. As the “golden copy” is stored on a local server and backed up locally, this computer or storage may be stolen, infected with viruses, or otherwise compromised. Having multiple servers also increases the overall exposure of the system to security breaches. Additionally, locally encrypting the data or the system further complicates the replication and synchronization of central servers 170 and decreases performance. Therefore, data in a distributed server implementation is vulnerable and maintaining compliance can be difficult.



FIG. 2 illustrates a centralized server system 200 in the prior art. The centralized server system 200 includes a branch office 210 and a central office 220 coupled by a communication network 230. The communication network 130 forms a WAN between the branch office 210 and the central office 220.


Typically, the central servers 260 in the central office 220 store the organization's data. Computers 240 make requests for the data from the central servers 260 over the communication network 230. The central servers 260 then return the data to the computers 240 over the communication network 230. Typically, the central servers 260 are not encrypted. The central servers 260 are usually maintained in a secure location such as a locked building requiring a hand scan or an iris scan for entry to prevent theft of the hard disks on which data is stored. This is a more secure system because the computers 240 contain only a small amount of unencrypted data that can be breached if, for example, the computer is stolen, resold, or infected by a virus.


The communication network 230 typically comprises a private network (e.g., a leased line network) or a public network (e.g., the Internet). The connections to the communication network 230 from the branch office 210 and the central office 220 typically cause a bandwidth bottleneck for exchanging the data over the communication network 230. The exchange of the data between the branch office 210 and the central office 220, in the aggregate, will usually be limited to the bandwidth of the slowest link in the communication network 230.


For example, the router 250 connects to the communication network 230 by a T1 line, which provides a bandwidth of approximately 1.544 Megabits/second (Mbps). The router 270 connects to the communication network 230 by a T3 line, which provides a bandwidth of approximately 45 Megabits/second (Mbps). Even though the communication network 230 may provide an internal bandwidth greater than 1.544 Mbps or 45 Mbps, the available bandwidth between the branch office 210 and the central office 220 is limited to the bandwidth of 1.544 Mbps (i.e., the T1 connection). Connections with higher bandwidth to relieve the bandwidth bottleneck across the communication network 230 are available, but are generally expensive and have limited availability.


Moreover, many applications do not perform well over the communication network 230 due to the limited available bandwidth. Developers generally optimize the applications for performance over a local area network (LAN) which typically provides a bandwidth between 10 Mbps to Gigabit/second (Gbps) speeds. The developers of the applications assume small latency and high bandwidth across the LAN between the applications and the data. However, the latency across the communication network 130 typically will be 100 times that across the LAN, and the bandwidth of the communication network 230 will be 1/100th of the LAN.


Furthermore, although FIG. 1 and FIG. 2 illustrate a single branch office and a single central office, multiple branch offices and multiple central offices exacerbate the previously discussed problems. For example, in a centralized server implementation having multiple branches, computers in each of the multiple branch offices make requests over the WAN to central servers for the organization's data. The data transmitted by the central servers in response to the requests quickly saturate the available bandwidth of the central office's connection to the communication network, further decreasing application performance and data access at the multiple branch offices. In a distributed server implementation having multiple branches, the cost to provide branch servers in each of the multiple branch offices increases, as well as the problems of licensing, security vulnerabilities, patching activities, and data replication and synchronization. Moreover, different branches may simultaneously attempt to modify the same piece of information. Maintaining coherency in a distributed implementation requires complex and error prone protocols.


As well as implementing centralized servers or distributed servers, organizations also implement mechanisms for caching to improve application performance and data access. A cache is generally used to reduce the latency of the communication network (e.g., communication network 230) forming the WAN (i.e., because the request is satisfied from the local cache) and to reduce network traffic over the WAN (i.e., because responses are local, the amount of bandwidth used is reduced).


Web caching, for example, is the caching of web documents (i.e., HTML pages, images, etc.) in order to reduce web site access times and bandwidth usage. Web caching typically stores unencrypted local copies of the requested web documents. The web cache satisfies subsequent requests for the web documents if the requests meet certain predetermined conditions.


One problem with web caching is that the web cache is typically only effective for rarely modified static web documents. For dynamic documents, there is a difficult tradeoff between minimizing network traffic and the risk of the web cache serving up stale data. The web cache may serve stale data because the web cache responds to requests without consulting the server.


Another problem is that the web cache does not recognize that two otherwise identical documents are the same if they have a different Uniform Resource Locator (URL). The web cache does not consider the content or context of the documents. Thus, the web cache caches the documents by URL or filename without a determination of the content or context of the document. Moreover, the web cache stores entire objects (such as documents) and cache-hits are binary: either a perfect match or a miss. Even where only small changes are made to the documents, the web cache does not use the cached copy of the documents to reduce network traffic.


SUMMARY

A network memory system for ensuring compliance is disclosed. The network memory system comprises a first appliance that encrypts data and stores the encrypted data in a first memory device. The first appliance also determines whether the original data is available in a second appliance in encrypted or unencrypted form and transmits a store instruction comprising the original data based on the determination that the first data does not exist in the second appliance. The second appliance receives the store instruction comprising the first data from the first appliance, encrypts the first data, and stores the encrypted data in a second memory device. The second appliance subsequently receives a retrieve instruction comprising an index, or location indicator, at which the encrypted first data is stored, processes the retrieve instruction to obtain encrypted response data, and decrypts the encrypted response data, and transmits the decrypted response data to a computer.


In some embodiments, the second appliance transmits the decrypted response data. The first appliance may receive data from at least one computer. The data may be encrypted using an algorithm such as Advanced Encryption Scheme, Data Encryption Scheme, or Triple Data Encryption Scheme. The second appliance may combine the encrypted response data with a key stream. In some embodiments, the first appliance stores the encrypted data at the index independent of an application or data context.


A method for ensuring compliance in a network memory is also disclosed. The method comprises encrypting data in a first appliance and storing the encrypted data in a first memory device. The method further comprises determining whether the original data is available in a second appliance in encrypted or unencrypted form, transmitting a store instruction comprising the original data from the first appliance, and receiving the store instruction into the second appliance, encrypting the first data, and storing the encrypted first data in a second memory device. Additionally, the method comprises receiving a retrieve instruction indicating an index at which the encrypted first data is stored into the second memory device, in the second appliance, processing the retrieve instruction to obtain encrypted response data, and decrypting the encrypted response data.


A software product for ensuring network compliance is also disclosed. The software product comprises software operational when executed by a processor to direct the processor to encrypt data in a first appliance, store the encrypted data in a memory device, determine whether the original data is available in a second appliance in encrypted or unencrypted form, and transmit a store instruction comprising the original first data from the first appliance. The software is further operational when executed by a processor to receive the store instruction into the second appliance, encrypt the data, store the encrypted data in a second memory device, receive a retrieve instruction into the second appliance, the retrieve instruction comprising an index at which the encrypted data is stored, processing the retrieve instruction to obtain encrypted response data in the second appliance, and decrypt the encrypted response data in the second appliance.





BRIEF DESCRIPTION OF THE DRAWINGS


FIG. 1 illustrates a distributed server system in the prior art;



FIG. 2 illustrates a centralized server system in the prior art;



FIG. 3 illustrates a network memory system, in an exemplary implementation of the invention;



FIG. 4 illustrates a message sequence chart for the network memory system where a response to a data request is not locally accessible to a branch appliance, in an exemplary implementation of the invention;



FIG. 5 illustrates data structures for the network memory system to determine whether a portion of the data is locally accessible to the branch appliance, in an exemplary implementation of the invention;



FIG. 6 illustrates a message sequence chart for the network memory system where the response to the data request is locally accessible to the branch appliance, in an exemplary implementation of the invention;



FIG. 7A and FIG. 7B illustrate a message sequence chart for the network memory system where a portion of the response to the data request is locally accessible to the branch appliance, in an exemplary implementation of the invention;



FIG. 8 illustrates a block diagram of the branch appliance, in an exemplary implementation of the invention;



FIG. 9 illustrates a block diagram of a central appliance, in an exemplary implementation of the invention;



FIG. 10 illustrates a network memory system between a first office, a second office, and a third office, in an exemplary implementation of the invention; and



FIG. 11 illustrates a message sequence chart for the network memory system for discovery and reconciliation, in an exemplary implementation of the invention.



FIG. 12 illustrates a flowchart for the central appliance or the branch appliance for decryption using a secret key, in an exemplary implementation of the invention.



FIG. 13 illustrates a flowchart for the central appliance or the branch appliance for decryption using a key stream, in an exemplary implementation of the invention.





DETAILED DESCRIPTION

The embodiments discussed herein are illustrative of one example of the present invention. As these embodiments of the present invention are described with reference to illustrations, various modifications or adaptations of the methods and/or specific structures described may become apparent to those skilled in the art. All such modifications, adaptations, or variations that rely upon the teachings of the present invention, and through which these teachings have advanced the art, are considered to be within the scope of the present invention. Hence, these descriptions and drawings should not be considered in a limiting sense, as it is understood that the present invention is in no way limited to only the embodiments illustrated.


To provide improved application performance and data access, the network memory system generally comprises a first appliance and a second appliance. The first appliance receives data and determines whether a portion of the data is locally accessible to the second appliance. The first appliance generates an instruction based on the determination and transfers the instruction to the second appliance through the communication network.


The network memory system provides that the second appliance processes the instruction to obtain the data and transfers the data to a computer. The data may be locally accessible to the second appliance, and the transfer to the computer may occur faster than transferring the data over the communication network. Accordingly, the second appliance transfers the data to computer without the first appliance transferring the data over the communication network that may have a high latency and low bandwidth. Thus, the network memory system operates to reduce latency and network traffic over the communication network.



FIG. 3 illustrates a network memory system 300, in an exemplary implementation of the invention. The network memory system 300 includes a branch office 310, a central office 320, and a communication network 330. The branch office 310 includes computers 340, a branch appliance 350, and a router 360. The central office 320 includes central servers 370, a central appliance 380, and a router 390.


In the branch office 310, the computers 340 are linked to the branch appliance 350. The branch appliance 350 is linked to the router 360. The router 360 is coupled to the communication network 330. In the central office 320, the central servers 370 are linked to the central appliance 380. The central appliance 380 is linked to the router 390. The router 390 is coupled to the communication network 330.


The principles discussed herein are equally applicable to multiple branch offices (not shown) and to multiple central offices (not shown). For example, the network memory system 300 may include multiple branch offices and/or multiple central offices coupled to the communication network 330. Branch office/branch office communication and central office/central office communication, as well as multi-appliance and/or multi-node communication and bi-directional communication are further within the scope of the disclosure. However, for the sake of simplicity, the disclosure illustrates the network memory system 300 having the single branch office 310 and the single central office 320, and the respective branch office 310/central office 320 communication.


The communication network 330 comprises hardware and/or software elements that enable the exchange of information (e.g., voice and data) between the branch office 310 and the central office 320. Some examples of the communication network 330 are a private wide-area network (WAN), and the Internet. Typically connections from the branch office 310 to the communication network 330 (e.g., from the router 360 and the router 390) are ISDN, T1 lines (1.544 Mbps), and possibly broadband connections such as digital subscriber lines (DSL) and cable modems. Other examples are T3 lines (43.232 Mbps), OC3 (155 Mbps), and OC48 (2.5 Gbps), although more costly and more likely used for interconnection at the central office 320 or as the backbone of the communication network 330.


The branch appliance 350 comprises hardware and/or software elements configured to receive data (e.g., email, files, and databases transactions), determine whether a portion of the data is locally accessible to an appliance (e.g., the central appliance 380), generate an instruction based on the determination, and transfer the instruction to the appliance. The branch appliance 350 also comprises hardware and/or software elements configured to receive an instruction from an appliance (e.g., the central appliance 380), process the instruction to obtain data, and transfer the data to a computer (e.g., the computers 340). One example of the branch appliance 350 is described below with respect to FIG. 8. The operations of the branch appliance 350 are discussed in further detail below in FIGS. 4, 5, 6, and 7A-7B.


Locally accessible data comprises any data transferable to the computer (e.g., the computers 340 and the central servers 370) by an appliance (e.g., the branch appliance 350 and the central appliance 380) without transferring the data over the communication network 330. In some examples, the locally accessible data is stored in random access memory (RAM) in the branch appliance 350, on a hard drive in the branch appliance 350, and a combination of data stored in RAM and on one or more hard drives in the branch appliance 350. In another example, the locally accessible data is accessible by the branch appliance 350 over a communication network (other than the communication network 330), such as data stored in a network attached storage (NAS) device that is internal or external to the branch office 310. In still another example, the locally accessible data is stored in a database. The database may be stored in RAM, on a hard disk, a combination of RAM and hard disks, in a NAS device, and/or in other optical and flash storage devices.


The instruction comprises any message or signal that indicates to an appliance (e.g., the branch appliance 350 and the central appliance 380) an action to perform with the data. Some examples of the instruction indicate to the appliance to store the data, to retrieve the data, and to forward the data to the computer (e.g., the central servers 370 and the computers 340). The instruction may be explicit or implicit based on instructions indicating to store or retrieve the data. In some embodiments, the instruction indicates an index within a database for storing and retrieving the data.


The central appliance 380 comprises hardware and/or software elements configured to receive data, determine whether a portion of the data is locally accessible to an appliance (e.g., the branch appliance 350), generate an instruction based on the determination, and transfer the instruction to the appliance. The central appliance 380 also comprises hardware and/or software elements configured to receive an instruction from an appliance (e.g., the branch appliance 350), process the instruction to obtain the data, and transfer the data to a computer (e.g., the central servers 370). One example of the central appliance 380 is described below with respect to FIG. 9. The operations of the central appliance 380 are discussed in further detail below in FIGS. 4, 5, 6, and 7A-7B.


As illustrated, the branch appliance 350 is configured in-line (or serially) between the computers 340 and the router 360. The central appliance 380 is also configured serially between the central servers 370 and the router 390. The branch appliance 350 and the central appliance 380 transparently intercept network traffic between the computers 340 and the central servers 370. For example, the central appliance 380 transparently intercepts data sent from the central servers 370 and addressed to the computers 340. The computers 340 and the central servers 370 advantageously require no additional configuration because the branch appliance 350 and the central appliance 380 operate transparently.


Alternatively, the branch appliance 350 and the central appliance 380 are configured as an additional router or gateway. As a router, for example, the branch appliance 350 appears to the computers 340 as an extra hop before the router 360. In some embodiments, the branch appliance 350 and the central appliance 380 provide redundant routing or peer routing with the router 360 and the router 390. Additionally, in the bridge and router configurations, the branch appliance 350 and the central appliance 380 provide failure mechanisms, such as, fail-to-open (e.g., no data access) or fail-to-wire (e.g., a direct connection to the router 360).


It will be understood that the branch appliance 350 and the central appliance 380 perform bi-directional communication. For example, data sent to the branch appliance 350 from the central appliance 380 may be stored in a location locally accessible to the central appliance 380 and in a location locally accessible to the branch appliance 350. If the data is to be transferred again from the central appliance 380 to the branch appliance 350, the central appliance 380 may determine that the data is locally accessible to the branch appliance 350 and generate an instruction to the branch appliance 350 to retrieve the data. The central appliance 380 transfers the instruction to the branch appliance 350 and the branch appliance 350 processes the instruction to obtain the data. If later, the branch appliance 350 is to transfer the entire data back to the central appliance 380, the branch appliance 350 may use the fact that the central appliance 380 has before transferred the data to the branch appliance 350. The branch appliance 350 therefore determines that the data is locally accessible to the central appliance 380 and generates an instruction to the central appliance 380 to retrieve the data. The branch appliance 350 transmits the instruction to the central appliance 380 and the central appliance 380 processes the instruction to obtain the data. Therefore, an appliance (e.g., the branch appliance 350 and the central appliance 380) in the network memory system 300 advantageously uses data transferred to and from the appliance to reduce network traffic with other appliances in the network memory system 300.


The network memory system 300 advantageously provides increased productivity, reduced IT costs, and enhanced data integrity and compliance. For example, the network memory system 300 achieves the simple administration of centralized server systems whereby the central servers 370 store the primary copy of the data. The network memory system 300 improves application performance and data access in the branch office 310 and central office 320 because not every response to a data request travels over the communication network 330 from the central servers 370. The branch appliance 350 and the central appliance 380 also store to and retrieve from a local copy of the data for subsequent exchanges of the data.


In addition to enhanced performance, network memory system 300 provides the increased compliance of centralized server systems. The branch appliance 350 encrypts data, stores the encrypted data within the local copy in the branch appliance 350 or a NAS device, and transmits the data to the central appliance 380. The branch appliance 350 also retrieves the encrypted response data from the local copy per an instruction from the central appliance 380, decrypts the response data, and forwards the response data to the computers 340. The branch appliance 350 may also determine whether the data is locally accessible to the central appliance 380.


The central appliance 380 may likewise receive an instruction from the branch appliance 350 to store encrypted data in a local copy such that is locally accessible to the central servers 370. The central appliance 380 may receive unencrypted data from central servers 370, encrypt the data, and store the data in the local copy. The central appliance 380 is configured to determine whether the data is locally accessible to the branch appliance 350. The central appliance 380 may also transmit a store instruction and encrypted data to the branch appliance 350. The central appliance 380 is further configured to decrypt the data before transmitting the data to the central servers 370. Because a master copy is stored in the central servers 370, locally accessible data is encrypted at the branch office 310 without the replication and synchronization problems of distributed server systems.


The branch appliance 350 and/or the central appliance 380 may encrypt the data using the Advanced Encryption Scheme (AES) algorithm, the Data Encryption Scheme (DES) algorithm, the Triple DES algorithm, or the like.


Additionally, the network memory system 300 does not cache the data in the traditional sense. The data may be retrieved locally even if the URL or filename for the data is different because the data may be identified by a pattern for the data itself and not by the URL or filename. Furthermore, unlike web caching, the network memory system 300 ensures that the data is coherent by forwarding messages (e.g., data requests and responses) between the computers 340 and the central servers 370. For example, web caching operates by locally intercepting messages for an authoritative source (e.g., a web server) and responding to the messages such that the web server potentially never sees the messages. In some cases, particularly with dynamic content, the locally cached copy may be stale or out-of-date. Advantageously, the network memory system 300 provides the data coherency and up-to-date data by the transparent operation of the network memory system 300 and the principle in which messages are transferred end-to-end (e.g., from computers 340 to the central servers 370), even though the messages and/or the data may not traverse the communication network 330.


The network memory system 300 does not have the higher cost of distributed server systems because the branch appliance 350 and the central appliance 380 provide benefits across all applications and displace several distributed devices and caches, particularly in multiple branch implementations. In some embodiments, the branch appliance 350 and the central appliance 380 provide internal storage for a secondary copy of the data. The network memory system 300 also reduces the hardware and license costs for the branch office 310 and the central office 320 by eliminating the need for the numerous distributed devices. Further, the network memory system 300 minimizes the security vulnerabilities and patching activities commonly associated with the distributed systems. Management of the branch appliance 350 and the central appliance 380 is simpler than the management of a remote distributed server. Unlike remote servers, there is no need to configure user accounts, permissions, and authentication schemes on the branch appliance 350 and the central appliance 380.



FIG. 4 illustrates a message sequence chart for the network memory system 300 where a response data 425 to a data request 410 is not locally accessible to the branch appliance 350, in an exemplary implementation of the invention. In this example, a computer 340 transmits the data request 410 through the branch appliance 350 and the central appliance 380 to a central server 370. Some examples of the data request 410 are requests for an email attachment, a file, a web page, and a database query.


In sequence 415, the central servers 370 process the data request 410, and in sequence 420, the central servers 370 generate the response data 425 based on the data request 410. Some examples of the response data 425 are an email message and attachment, a file, a web page, and results retrieved or obtained from the database query. The central servers 370 then transmit the response data 425 to the central appliance 380. Alternatively, in some embodiments, the central servers 370 address the response data 425 directly to the computers 340, however, during transmission, the central appliance 380 transparently intercepts the response data 425. In sequence 430, the central appliance 380 processes the response data 425 to determine whether a portion of the response data 425 is locally accessible to the branch appliance 350.



FIG. 5 illustrates data structures for the network memory system 300 to determine whether a portion of the data is locally accessible to the branch appliance 350, in an exemplary implementation of the invention. The data structures include a fine signature hash table (SHT) 505, a coarse signature hash table (SHT) 525, and flow history pages (FHPs) 545. The fine SHT 505 includes one or more entries comprising a check field 510, a page field 515, and a byte field 520. The coarse SHT 525 includes one or more entries comprising a check field 530, a page field 535, and a byte field 540. The FHPs 545 include one or more pages (e.g., page 1-M). Each page (e.g., page N) includes page state information 550 and stores data 555. The FHPs 545 may be encrypted using the Advanced Encryption Scheme (AES) algorithm, the Data Encryption Scheme algorithm (DES), the Triple DES algorithm, or the like.


An appliance of the network memory system 300 (e.g., the branch appliance 350 and the central appliance 380) calculates hashes at every byte boundary of a data flow (e.g., the response data 425) to be sent across the communication network 330. In some embodiments, the data flow includes packets that are in the same Internet Protocol (IP) flow, as defined by the IP header five tuple of source address, source port, destination address, destination port, and protocol. The hashes may be influenced by preceding bytes in the data flow. For example, the hashes are influenced by approximately the n previous bytes, where n determines the fingerprint size. Some examples of calculating the hashes are cyclical redundancy checks (CRCs) and checksums over the previous n bytes of the data flow. In some embodiments, rolling implementations of CRCs and checksums are used where a new byte is added, and a byte from n bytes earlier is removed. To maximize the ability to determine whether a portion of the data flow is available in another appliance in the network memory system 300, the hash calculation may span across successive IP packets in the data flow. In other embodiments, the hash calculation ignores patterns that span one or more IP packet boundaries in the data flow, and the hashes are calculated within a single IP packet.


Each calculated hash is filtered by a fine filter 560 and a coarse filter 565. The appliance designates the locations in the data flow which meet the fine and coarse filter criteria as fine and coarse sync-points, respectively. The fine filter 560 and the coarse filter 565 have different filter criteria. Typically, the filter criteria for the coarse filter 565 are more restrictive and may be used to further filter those hashes which pass the fine filter. In other words, the fine filter produces a fine comb of sync-points and the coarse filter produces a coarse comb of sync-points. One example of the filter criteria is the null filter which allows results in sync-points at all locations. In another example, the filter criteria declares a fine sync-point when the top five bits of the hashes are all zeros and a coarse filter criteria which stores or compares hashes when the top ten bits of the hashes are all zeros. The hash at the fine sync-points index the fine SHT 505 and the hash at the coarse sync-points index the coarse SHT 525. For example, the index could be derived from the hash by using a number of low order bits from the hash. The filter criteria affect the sizing of the SHTs 505 and 525 and the probability of matching a hash in the SHTs 505 and 525. The more sync-points that are generated the easier repeated data is identified but, the larger the tables (i.e., the SHTs 505 and 525) need to be in order to index a given amount of information for the data flow. Having a coarse and fine table helps optimize this tradeoff. Alternative implementations may use a single table or multiple tables.


The fine SHT 505 is populated with hashes as the data 555 (e.g., the response data 425) is stored and when the data 555 is recalled from disk or other locally accessible storage. The fine SHT 505 finely indexes the data 555. In some embodiments, the fine SHT 505 holds approximately one entry for every 100 bytes of the data 555. The coarse SHT 525 is populated as the data 555 is stored and is coarsely indexed. For example, the coarse SHT 525 may hold one entry for approximately every 4 kilobytes (KB) of the data 555. The fine SHT 505 and the coarse SHT 525 may be considered short term and long term memory index structures, respectively.


The appliance of the network memory system 300 stores all or part of the calculated hashes in or compares all or part of the hashes to the check field 510 in the SHTs 505 and 525. For example, the central appliance 380 verifies a “hit” in the fine SHT 505 by comparing the entire calculated hash or a number of residual bits of the calculated hash to the check field 510. If the central appliance 380 finds no matching hashes in the fine SHT 505 or in the coarse SHT 525, the central appliance 380 determines that the response data 425 is not locally accessible to the branch appliance 350. Each calculated hash for the response data 425 in the fine SHT 505 and the coarse SHT 525 is stored or compared depending on the filter criteria for the fine filter 560 and the coarse filter 565.


The appliance of the network memory system 300 indexes each entry in the fine SHT 505 and the coarse SHT 525 to a page (e.g., by setting the page field 515 and the page field 535 to address page N) and byte offset (e.g., by setting the byte field 520 and the byte field 540 to a byte offset of the data 555) in the FHPs 545. For example, the central appliance 380 stores the response data 425 in the FHPs 545 at the page pointed to by the page field 515 and 535 at the byte offset indicated by the byte field 520 and 540. The byte field 520 of each hash in the fine SHT 505 for the response data 425 points to the start of a fine sync-point. The byte field 540 of each hash in the coarse SHT 525 for the response data 425 points to the start of a coarse sync-point.


In this example, the branch appliance 350 includes a fine SHT 505, a coarse SHT 525, and a FHP 545 data structure, and the central appliance 380 includes a fine SHT 505, a coarse SHT 525, and a FHP 545 data structure. Each appliance in the network memory system 300 maintains the separate data structures, with may include separate filter criteria for the fine filter 560 and the coarse filter 565. The page state information 550, in the FHP 545 of each appliance in the network memory system 300, includes page parameters, page ownership permissions, peer state, and a list of valid byte ranges for each appliance in the network memory system 300. The page state information 550 tracks the local state of the page (e.g., the FHP 545 in the branch appliance 350, and what parts of the page are used) and the remote state of the page at peers (e.g., the central appliance 380, and what part of the page in the branch appliance 350 is used by the central appliance 380).


The branch appliance 350 and the central appliance 380 each write the data 555 to an assigned page (e.g., the page N or the page N+1) and may reference a page assigned to another appliance in the network memory system 300. Appliances in the network memory system 300 may discover and reconcile the FHPs 545 assigned to other appliances as explained below with regard to FIGS. 9 and 10.


Referring again to FIG. 4, the central appliance 380 proceeds with the determination that no portion of the response data 425 is locally accessible to the branch appliance 350. In sequence 435, the central appliance 380 generates a store instruction 440. The store instruction 440 indicates to the branch appliance 350 to store the response data 425 at an index in a database. The central appliance 380 attaches the store instruction 440 to the response data 425. The central appliance 380 then transmits the response data 425, which may be encrypted, with the store instruction 440 to the branch appliance 350.


In sequence 445, the branch appliance 350 processes the response data 725 with the store instruction 440. In sequence 450, based on the store instruction 440, the branch appliance 350 stores the response data 425 in the branch appliance 350 at the index within the database. In this example, the branch appliance 350 stores the response data 425 in the FHPs 545 at the page and at a particular byte offset indicated by the index. Sequence 450 additionally includes encrypting the FHPs 545. In sequence 455, the branch appliance 350 forwards the response data 425 to the computer 340. As discussed previously, the branch appliance 350 may forward the data to the computer based on explicit and implicit instructions.



FIG. 6 illustrates a message sequence chart for the network memory system 300 where a response data 625 to a data request 610 is locally accessible to the branch appliance 350, in an exemplary implementation of the invention. In this example, the computer 340 transmits the data request 610 to the central servers 370 through the branch appliance 350 and the central appliance 380. In sequence 615, the central servers 370 process the data request 610. In sequence 620, the central servers 370 generate a response data 625 based on the data request 610. The central servers 370 then transmit the response data 625 to the central appliance 380.


In sequence 630, the central appliance 380 processes the response data 625 to determine whether a portion of the response data 625 is locally accessible to the branch appliance 350. The central appliance 380 again generates hashes for the response data 625, as previously described with respect to FIGS. 4 and 5. The central appliance 380 filters the generated hashes through the fine filter 560 and the coarse filter 565 to determine fine and/or coarse sync-points. The central appliance 380 looks up the fine sync-points in the fine SHT 505 and the coarse sync-points in the coarse SHT 525. If any of the hashes for the response data 625 match (i.e., the check bytes match in either the fine SHT 505 and/or the coarse SHT 525), then additional checks (such as direct forward comparisons and backward memory comparisons between the response data 625 and the data 555 in the FHPs 545) may also be made to determine the size of the matching region. Further checks using the page state information 550 determine which portion of the response data 625 is locally accessible to the branch appliance 350.


Based on the determination that the entire response data 625 is locally accessible to the branch appliance 350, in sequence 635, the central appliance 380 generates a retrieve instruction 640 that indicates to the branch appliance 350 to retrieve the response data 625 at an index within the database. The central appliance 380 then transmits only the retrieve instruction 640 to the branch appliance 350. In this manner, the central appliance 380 optimizes network traffic over the communication network 330. If the retrieve instruction 640 is smaller in size than the response data 625, the central appliance 380 transmits the retrieve instruction 640. If the retrieve instruction 640 is larger than the response data 625, the central appliance 380 transmits the response data 625 instead.


In sequence 645, the branch appliance 350 processes the retrieve instruction 640. In sequence 650, based on the retrieve instruction 640, the branch appliance 350 retrieves the response data 625 at the index within the database. Sequence 650 includes decrypting the FHPs 545 in which the response data 625 is stored. In sequence 655, the branch appliance 350 forwards the response data 625 to the computer 340.



FIG. 7A and FIG. 7B illustrate a message sequence chart for the network memory system 300 where a portion of a response data 725 to a data request 710 is locally accessible to the branch appliance 350, in an exemplary implementation of the invention. The computer 340 transmits the data request 710 to the central servers 370 through the branch appliance 350 and the central appliance 380. In sequence 715, the central servers 370 process the data request 710. In sequence 720, the central servers 370 generate a response data 725 based on the data request 710. The central servers 370 then transmit the response data 725 to the central appliance 380.


In sequence 730, the central appliance 380 processes the response data 725 to determine whether a portion of the response data 725 is locally accessible to the branch appliance 350. The central appliance 380 computes hashes for the response data 725 and filters the hashes through the fine filter 560 and the coarse filter 565 to determine any fine and coarse sync-points. The central appliance 380 then looks up any fine sync-points in the fine SHT 505 and coarse sync-points in the coarse SHT 525. In this example, only a portion of the response data 725 is locally accessible to the branch appliance 350, meaning that although the central appliance 380 finds at least one match in the SHTs 505 and 525, additional checks (such as the direct forward comparison and the backward memory comparison with the response data 725 and the data 555) determine that only a portion of the response data 725 is locally accessible to the branch appliance 350.


The central appliance 380 stores the generated hashes for the non-locally accessible portion of the response data 725 (otherwise known as the deltas) in the SHTs 505 and 525, and stores the deltas in the FHPs 545. The central appliance 380 additionally encrypts the FHPs 545. The central appliance 380 will transmit the deltas (i.e., the portion of the response data 725 that is not locally accessible) to the branch appliance 350.


In sequence 735, the central appliance 380 generates retrieve and store instructions 740. The retrieve instruction indicates to the branch appliance 350 to retrieve the locally accessible portion of the response data 725 at an index within the database. The store instruction indicates to the branch appliance 350 to store the deltas at an index within the database. The store instruction may also indicate to the branch appliance 350 to store another copy of the portion of the response data 725 locally accessible to the branch appliance 350 with the deltas. The entire response data 725 will then be locally accessible in the database to the branch appliance 350. The central appliance 380 attaches the deltas to the retrieve and store instructions 740. The central appliance 380 then transmits the non-locally accessible portion of the response data 725 with retrieve and store instructions 740 to the branch appliance 350.


In sequence 745, the branch appliance 350 processes the non-locally accessible portion of the response data 725 with retrieve and store instructions 740. In sequence 750, based on the retrieve instruction, the branch appliance 350 retrieves the locally accessible portion of the response data 725 at the index in the database. In sequence 755, the branch appliance 350 obtains the response data 725 from the retrieved locally accessible portion and the transferred deltas (i.e., the transferred non-locally accessible portion of the response data 725). To obtain the data, the branch appliance 350 decrypts the response data 725. In sequence 760, based on the store instruction, the branch appliance 350 stores the deltas (and potentially the retrieve locally accessible portion of the response data 725) at the index in the database. If the deltas are not encrypted, the branch appliance 350 further encrypts the deltas. In sequence 765, the branch appliance 350 transmits the entire response data 725 to the computer 340.


Alternatively, in addition to the examples in FIGS. 4, 5, 6, and 7A-7B illustrating a request for the data originating from the computer 340 to the central servers 370, the computer 340 may also transmit data to the branch appliance 350 addressed to the central servers 370. The branch appliance 350 determines whether a portion of the data is locally accessible to the central appliance 380. Then, for example, if the data is locally accessible to the central appliance 380, the branch appliance 350 generates a retrieve instruction indicating to the central appliance 380 to retrieve the data and forward the data to the central servers 370.


In still further embodiments, the instruction may indicate a plurality of indexes. Referring again to FIG. 7B, in sequence 750, based on the retrieve instruction indicating a plurality of indexes for the response data 725, the branch appliance 350 may retrieve the locally accessible portion of the response data 725 at different locations based on the plurality of index. For example, the branch appliance 350 may retrieve a portion of the response data 725 from RAM, a portion from a hard disk, and a portion from a NAS device. Similarly, in sequence 760, based on the store instruction indicating a plurality of indexes for the response data 725, the branch appliance 350 may stores the deltas in the database and after obtaining the entire response data 725, store the entire response data 725 in a different location (e.g., in a different location in the database, in a disk drive, or in a NAS device) than the previously locally accessible portion.



FIG. 8 illustrates a block diagram of the branch appliance 350, in an exemplary implementation of the invention. The branch appliance 350 includes a processor 810, a memory 820, a WAN communication interface 830, a LAN communication interface 840, and a database 850. A system bus 880 links the processor 810, the memory 820, the WAN communication interface 830, the LAN communication interface 840, and the database 850. Line 860 links the WAN communication interface 830 to the router 360 (in FIG. 3). Line 870 links the LAN communication interface 840 to the computers 340 (in FIG. 3).


The database 850 comprises hardware and/or software elements configured to store data in an organized format to allow the processor 810 to create, modify, and retrieve the data. The database 850 may organize the data to enable the determination of whether a portion of the data is locally accessible to an appliance, and to enable quick retrieval of locally accessible data to the branch appliance 350. The hardware and/or software elements of the database 850 may include storage devices, such as RAM, hard drives, optical drives, flash memory, and magnetic tape. In some embodiments, the branch appliance 350 implements a virtual memory system with linear addresses, the locally accessible data, and the data structures discussed with respect to FIG. 5 in the database 850.



FIG. 9 illustrates a block diagram of the central appliance 380, in an exemplary implementation of the invention. The central appliance 380 includes a processor 910, a memory 920, a WAN communication interface 930, a LAN communication interface 940, and a database 950. A system bus 980 links the processor 910, the memory 920, the WAN communication interface 930, the LAN communication interface 940, and the database 950. Line 960 links the WAN communication interface 930 to the router 390 (in FIG. 3). Line 970 links the LAN communication interface 940 to the central servers 370 (in FIG. 3). In some embodiments, the branch appliance 350 and the central appliance 380 comprise the identical hardware and/or software elements. Alternatively, in other embodiments, the central appliance 380 may include hardware and/or software elements providing additionally processing, communication, and storage capacity.


Advantageously, the network memory system 300 improves application performance and data access. In some embodiments, by storing a secondary copy of the data locally accessible to the branch appliance 350 and the central appliance 380, the network memory system 300 minimizes the effects of latency and reduces network traffic over the communication network 330 to the central servers 370. Additionally, while the central servers 370 maintain the primary copy of the data, the central servers 370 potentially do not transfer the actual data over the communication network 330 for every request/response. Furthermore, accelerated access to the data locally accessible to the branch appliance 350 and the central appliance 380 is not limited to a particular application or data context.


In some embodiments, the network memory system 300 includes a secure tunnel between the branch appliance 350 and the central appliance 380. The secure tunnel provides encryption (e.g., IPsec) and access control lists (ACLs). Additionally, in other embodiments, the secure tunnel includes compression, such as header and payload compression. The secure tunnel may provide fragmentation/coalescing optimizations along with error detection and correction.



FIG. 10 illustrates a network memory system 1000 between a first office 1010, a second office 1030, and a third office 1060, in an exemplary implementation of the invention. The first office 1010 includes a computer 1015 and a first network memory appliance (NMA) 1020. The second office 1030 includes a computer 1040 and a second NMA 1050. The third office 1060 includes a third NMA 1070 and a server 1080. The first office 1010 is linked to the second office 1030 and the third office 1060 (e.g., through routers not shown). The second office 1030 is also linked to the third office 1060.


The first NMA 1020, the second NMA 1050, and the third NMA 1070 comprise hardware and/or software elements, similar to the branch appliance 350 and the central appliance 380, configured to receive data, determine whether the data is locally accessible to an appliance, generate an instruction based on the determination, and transfer the instruction to the appliance. The first NMA 1020, the second NMA 1050, and the third NMA 1070 also comprise hardware and/or software elements configured to receive an instruction from an appliance, process the instruction to obtain data, and transfer the data to a computer.


Advantageously, in this multi-office example, the network memory system 1000 provides for locally accessible data in each office. The first NMA 1020, the second NMA 1050, and the third NMA 1070 receive data, potentially destined for a computer and/or server in another office, and determine whether a portion of the data is locally accessible to an NMA in that office. To further enhance operation and the exchange of data between the first NMA 1020, the second NMA 1050, and the third NMA 1070, each NMA performs a discovery and reconciliation. During discovery and reconciliation the virtual memory map of the network memory system 1000 is updated. For example, each NMA updates the pages of the FHPs 545 in the NMA with references for data locally accessible in the network memory system 1000 and to which NMA the data is locally accessible.



FIG. 11 illustrates a message sequence chart for the network memory system 1000 for discovery and reconciliation, in an exemplary implementation of the invention. In this example, the computer 1015 in the first office 1010 transmits data to the first NMA 1020 for the first time addressed to the computer 1040 in the second office 1030. The first NMA 1020 transmits the data with a store instruction to the second NMA 1050 indicating to store the data in a database in the second NMA 1050. In sequence 1110, the second NMA 1050 stores the data in the database, and the second NMA 1050 transmits the data to the computer 1040.


The computer 1015 in the first office 1010 then transmits the same data to the first NMA 1020 addressed for the first time to the server 1080 in the third office 1060. The first NMA 1020 transmits the data with a store instruction to the third NMA 1070 indicating to store the data in a database in the third NMA 1070. In the sequence 1115, the third NMA 1070 stores the data in the database, and the third NMA 1070 transmits the data to the server 1080.


In sequence 1120, 1125, and 1130, the first NMA 1020, the second NMA 1050, and the third NMA 1070 perform discovery and reconciliation including update the virtual memory map. In this example, the first NMA 1020, the second NMA 1050, and the third NMA 1070 exchange information (e.g., the page state information 550) about which parts of the FHPs 545 each NMA has available locally. For example, to update the FHPs 545 in the second NMA 1050, the second NMA 1050 performs a discovery and reconciliation with the first NMA 1020 and the third NMA 1070. Similarly, each NMA performs discovery and reconciliation with every other peer NMA.


During the discovery and reconciliation between the second NMA 1050 and the first NMA 1020, for example, the second NMA 1050 discovers from the first NMA 1020 that the data (transmitted from the computer 1015 to the computer 1040 and the server 1080) is locally accessible to the third NMA 1070. The FHPs 545 of the first NMA 1020 include references to the data (e.g., in the page state information 550) and because the first NMA 1020 transferred the data to the third NMA 1070, the FHPs 545 indicate that the data is locally accessible to the third NMA 1070. The second NMA 1050 reconciles the references for the data in the FHPs 545 and further indicates that data is locally accessible to the third NMA 1070.


Referring again to FIG. 11, in sequence 1135, after the discovery and reconciliation in sequences 1120, 1125, and 1130, the computer 1040 in the second office 1030 transmits the data addressed to the server 1080 in the third office 1060. The data is intercepted by the second NMA 1050, and in sequence 1140, the second NMA 1050 determines whether a portion of the data is locally accessible to the third NMA 1070. Since the discovery and reconciliation, the FHPs 545 in the second NMA 1050 indicates that data is locally accessible to the third NMA 1070. In sequence 1145, the second NMA 1050 generates a retrieve instruction indicating to the third NMA 1070 to retrieve the data from an index within the database. The second NMA 1050 transfers the retrieve instruction to the third NMA 1070.


In sequence 1150, the third NMA 1070 processes the retrieve instruction. In sequence 1155, based on the retrieve instruction, the third NMA 1070 retrieves the data at the index within the database. In sequence 1160, the third NMA 1070 forwards the data to the server 1080.


Therefore, the network memory system 1000 provides improved application performance and data access between the first office 1010, the second office 1030, and the third office 1060. The network memory system 1000 provides access to locally accessible data, similar to distributed servers, without the complex management involved with replication and synchronization of the data among the distributed servers. Additionally, the network memory system 1000 reduces network traffic between the offices. Furthermore, discovery and reconciliation provides performance advantages by periodically or continuously updating the FHPs 545 in each NMA.



FIG. 12 illustrates a flowchart for the branch appliance 350 for decryption 1200, in an exemplary implementation of the invention. In other implementations of the invention, the central appliance 380 may perform decryption 1200. In step 1210, the branch appliance 350 receives a data request 610 for a FHP 545 that is locally accessible to the receiving appliance. In step 1220, the branch appliance 350 then reads the encrypted FHP 545 from the index within the database 850 or the database 950. This process may last five to ten milliseconds. To decrypt the FPH 545, the branch appliance 350 uses a secret key in step 1230. The decryption may last one to five milliseconds. The secret key may be stored in the memory 820 of the branch appliance 350. In step 1240, the branch appliance 350 decrypts the FHP 545 and makes the FHP 545 available to the computers 340 in a total time of about fifteen to twenty milliseconds.



FIG. 13 illustrates a flowchart for the branch appliance 350 for decryption 1300 using a key stream in an exemplary implementation of the invention. In other implementations of the invention, the central appliance 380 may perform decryption 1300. If the branch appliance uses a key stream, the time required to retrieve and decrypt a requested FHP 545 can be decreased. In step 1310, the branch appliance 350 receives a data request 610 for an encrypted FHP 545 that is locally accessible to the branch appliance 350. In step 1320, the branch appliance 350 then reads the encrypted FHP 545 from the index within the database 850. This process may last five to ten milliseconds. During this step, the branch appliance 350 also performs step 1330 to generate a key stream of “random” numbers generated using the secret key. The generation of the key stream may last one to five milliseconds and runs in parallel to step 1320.


In step 1340, the branch appliance 350 decrypts the FHP 545 by combining the FHP 545 with the key stream. For example, the branch appliance 350 may combine the FHP 545 and the key stream using an XOR function. In step 1350, the FHP 545 is available to the computers 340 in a total time of about five to ten milliseconds, about the same amount of time required to retrieve data in an unencrypted system. Thus, the performance of the network is not affected by the decryption of the response data 625 when a key stream is used.


The above-described functions can be comprised of executable instructions that are stored on storage media. The executable instructions can be retrieved and executed by a processor. Some examples of executable instructions are software, program code, and firmware. Some examples of storage media are memory devices, tape, disks, integrated circuits, and servers. The executable instructions are operational when executed by the processor to direct the processor to operate in accord with the invention. Those skilled in the art are familiar with executable instructions, processor(s), and storage media.


The above description is illustrative and not restrictive. Many variations of the invention will become apparent to those of skill in the art upon review of this disclosure. The scope of the invention should, therefore, be determined not with reference to the above description, but instead should be determined with reference to the appended claims along with their full scope of equivalents.

Claims
  • 1. A network memory system, comprising: a source-site appliance comprising a first processor and a first memory device, and configured to be coupled to a source-site computer via a source-site local area network; anda destination-site appliance comprising a second processor and a second memory device, and configured to be coupled to a destination-site computer via a destination-site local area network, the source-site computer in communication with the destination-site computer via a wide area network; the source-site appliance configured to intercept original data sent from the source-site computer to the destination-site computer, encrypt the original data to generate encrypted data, store the encrypted data in the first memory device, determine whether a representation of the original data exists in the second memory device, and transmit a store instruction comprising the original data if the representation of the original data does not exist in the second memory device; andthe destination-site appliance configured to receive the store instruction from the source-site appliance, encrypt the original data received with the store instruction at the destination-site appliance to generate encrypted received data, store the encrypted received data in the second memory device, subsequently receive a retrieve instruction comprising an index at which the encrypted received data is stored in the second memory device, process the retrieve instruction to obtain encrypted response data comprising at least a portion of the encrypted received data, and decrypt the encrypted response data.
  • 2. The network memory system of claim 1, wherein the destination-site appliance is further configured to transmit the decrypted response data to the destination-site computer.
  • 3. The network memory system of claim 1, wherein the destination-site appliance is configured to encrypt the original data using an Advanced Encryption Scheme algorithm.
  • 4. The network memory system of claim 1, wherein the destination-site appliance is configured to encrypt the original data using a Data Encryption Scheme algorithm.
  • 5. The network memory system of claim 1, wherein the destination-site appliance is configured to encrypt the original data using a Triple Data Encryption Scheme algorithm.
  • 6. The network memory system of claim 1, wherein the source-site appliance is configured to determine whether a representation of the original data exists in the second memory device by identifying sync points in the original data having matches in locally accessible data stored in the first memory device, performing at one or more of the sync points, a forward and backward memory comparison to identify a size of a matching region, and determining a non-locally accessible portion of the original data outside the matching region that is not locally accessible at the destination-site appliance.
  • 7. The network memory system of claim 6, wherein the source-site appliance is further configured to identify the sync points in the original data by (i) determining hash values corresponding to different byte locations of the original data, (ii) finely filtering the hash values using a fine filter to determine a finely filtered set of the hash values corresponding to fine sync points, and coarsely filtering the hash values using a coarse filter to determine a coarsely filtered set of the hash values corresponding to coarse sync points, and (iii) determining from the finely filtered set of the hash values and the coarsely filtered set of the hash values, a plurality of hash values matching hash values of the locally accessible data.
  • 8. A method for ensuring compliance in network memory, the method comprising: in a source-site appliance, intercepting original data sent from a source-site computer to a destination-site computer, the source-site appliance coupled to the source-site computer via a source-site local area network and the source-site computer in communication with the destination-site computer via a wide area network;encrypting the original data to generate encrypted data;storing the encrypted data in a first memory device within the source-site appliance;determining whether a representation of the original data exists in a destination-site appliance, the destination-site appliance coupled to the destination-site computer via a destination-site local area network;transmitting a store instruction comprising the original data from the source-site appliance based on the determination that the representation of the original data does not exist in the destination-site appliance;receiving the store instruction into the destination-site appliance;encrypting the original data received with the store instruction at the destination-site appliance to generate encrypted received data;storing the encrypted received data in a second memory device within the destination-site appliance;subsequently receiving a retrieve instruction into the destination-site appliance, the retrieve instruction comprising an index at which the encrypted received data is stored;in the destination-site appliance, processing the retrieve instruction to obtain encrypted response data comprising at least a portion of the encrypted received data; andin the destination-site appliance, decrypting the encrypted response data.
  • 9. The method of claim 8, further comprising transmitting the decrypted response data from the destination-site appliance to the destination-site computer.
  • 10. The method of claim 8, further comprising encrypting the original data using an Advanced Encryption Scheme algorithm.
  • 11. The method of claim 8, further comprising encrypting the original data using a Data Encryption Scheme algorithm.
  • 12. The method of claim 8, further comprising encrypting the original data using a Triple Data Encryption Scheme algorithm.
  • 13. The method of claim 8, wherein determining whether a representation of the original data exists in the second memory device comprises: identifying sync points in the original data having matches in locally accessible data stored in the first memory device;performing at one or more of the sync points, a forward and backward memory comparison to identify a size of a matching region; anddetermining a non-locally accessible portion of the original data outside the matching region that is not locally accessible at the destination-site appliance.
  • 14. The method of claim 13, wherein identifying the sync points in the original data comprises: determining hash values corresponding to different byte locations of the original data;finely filtering the hash values using a fine filter to determine a finely filtered set of the hash values corresponding to fine sync points, and coarsely filtering the hash values using a coarse filter to determine a coarsely filtered set of the hash values corresponding to coarse sync points; anddetermining from the finely filtered set of the hash values and the coarsely filtered set of the hash values, a plurality of hash values matching hash values of the locally accessible data.
  • 15. A network memory system comprising: a first non-transitory computer-readable storage medium storing first instructions that when executed causing a first processor to perform steps comprising: encrypting the original data to generate encrypted data;storing the encrypted data in a first memory device within the source-site appliance;determining whether a representation of the original data exists in a destination-site appliance, the destination-site appliance coupled to the destination-site computer via a destination-site local area network;transmitting a store instruction comprising the original data from the source-site appliance based on the determination that the representation of the original data does not exist in the destination-site appliance;a second non-transitory computer-readable storage medium storing second instructions that when executed causing a second processor to perform steps comprising: receiving the store instruction into the destination-site appliance;encrypting the original data received with the store instruction at the destination-site appliance to generate encrypted received data;storing the encrypted received data in a second memory device within the destination-site appliance;subsequently receiving a retrieve instruction into the destination-site appliance, the retrieve instruction comprising an index at which the encrypted received data is stored;in the destination-site appliance, processing the retrieve instruction to obtain encrypted response data comprising at least a portion of the encrypted received data; andin the destination-site appliance, decrypting the encrypted response data.
  • 16. The network memory system of claim 15, wherein the second instructions when executed cause the second processor to transmit the decrypted response data to the destination-site computer.
  • 17. The network memory system of claim 15, wherein encrypting the original data comprises applying an Advanced Encryption Scheme algorithm.
  • 18. The network memory system of claim 15, wherein encrypting the original data comprises applying a Data Encryption Scheme algorithm.
  • 19. The network memory system of claim 15, wherein determining whether a representation of the original data exists in the second memory device comprises: identifying sync points in the original data having matches in locally accessible data stored in the first memory device;performing at one or more of the sync points, a forward and backward memory comparison to identify a size of a matching region; anddetermining a non-locally accessible portion of the original data outside the matching region that is not locally accessible at the destination-site appliance.
  • 20. The network memory system of claim 15, wherein identifying the sync points in the original data comprises: determining hash values corresponding to different byte locations of the original data;finely filtering the hash values using a fine filter to determine a finely filtered set of the hash values corresponding to fine sync points, and coarsely filtering the hash values using a coarse filter to determine a coarsely filtered set of the hash values corresponding to coarse sync points; anddetermining from the finely filtered set of the hash values and the coarsely filtered set of the hash values, a plurality of hash values matching hash values of the locally accessible data.
CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation and claims the priority benefit of U.S. patent application Ser. No. 14/248,167 filed on Apr. 8, 2014, entitled “Data Encryption in a Network Memory Architecture for Providing Data Based on Local Accessibility,” which is a continuation and claims the priority benefit of U.S. patent application Ser. No. 13/757,548 filed on Feb. 1, 2013, entitled “Data Encryption in a Network Memory Architecture for Providing Data Based on Local Accessibility,” now U.S. Pat. No. 8,732,423 issued on May 20, 2014, which in turn is a continuation of, and claims the priority benefit of, U.S. patent application Ser. No. 11/497,026 filed on Jul. 31, 2006, entitled “Data Encryption in a Network Memory Architecture for Providing Data Based on Local Accessibility,” now U.S. Pat. No. 8,392,684 issued on Mar. 5, 2013, which is in turn a continuation-in-part of U.S. patent application Ser. No. 11/202,697 filed on Aug. 12, 2005, entitled “Network Memory Architecture for Providing Data Based on Local Accessibility,” now U.S. Pat. No. 8,370,583 issued on Feb. 5, 2013. The above applications are hereby incorporated by reference in their entirety.

US Referenced Citations (337)
Number Name Date Kind
4494108 Langdon, Jr. et al. Jan 1985 A
4612532 Bacon et al. Sep 1986 A
5023611 Chamzas et al. Jun 1991 A
5243341 Seroussi et al. Sep 1993 A
5307413 Denzer Apr 1994 A
5357250 Healey et al. Oct 1994 A
5359720 Tamura et al. Oct 1994 A
5373290 Lempel et al. Dec 1994 A
5483556 Pillan et al. Jan 1996 A
5532693 Winters et al. Jul 1996 A
5592613 Miyazawa et al. Jan 1997 A
5611049 Pitts Mar 1997 A
5627533 Clark May 1997 A
5635932 Shinagawa et al. Jun 1997 A
5652581 Furlan et al. Jul 1997 A
5659737 Matsuda Aug 1997 A
5675587 Okuyama et al. Oct 1997 A
5710562 Gormish et al. Jan 1998 A
5748122 Shinagawa et al. May 1998 A
5754774 Bittinger et al. May 1998 A
5802106 Packer Sep 1998 A
5805822 Long et al. Sep 1998 A
5883891 Williams et al. Mar 1999 A
5903230 Masenas May 1999 A
5955976 Heath Sep 1999 A
6000053 Levine et al. Dec 1999 A
6003087 Housel, III et al. Dec 1999 A
6054943 Lawrence Apr 2000 A
6081883 Popelka et al. Jun 2000 A
6175944 Urbanke et al. Jan 2001 B1
6295541 Bodnar et al. Sep 2001 B1
6308148 Bruins et al. Oct 2001 B1
6311260 Stone et al. Oct 2001 B1
6339616 Kovalev Jan 2002 B1
6374266 Shnelvar Apr 2002 B1
6434662 Greene et al. Aug 2002 B1
6438664 McGrath et al. Aug 2002 B1
6452915 Jorgensen Sep 2002 B1
6489902 Heath Dec 2002 B2
6587985 Fukushima et al. Jul 2003 B1
6618397 Huang Sep 2003 B1
6633953 Stark Oct 2003 B2
6643259 Borella et al. Nov 2003 B1
6650644 Colley et al. Nov 2003 B1
6653954 Rijavec Nov 2003 B2
6667700 McCanne et al. Dec 2003 B1
6674769 Viswanath Jan 2004 B1
6718361 Basani et al. Apr 2004 B1
6738379 Balazinski et al. May 2004 B1
6769048 Goldberg et al. Jul 2004 B2
6791945 Levenson et al. Sep 2004 B1
6856651 Singh Feb 2005 B2
6859842 Nakamichi et al. Feb 2005 B1
6862602 Guha Mar 2005 B2
6910106 Sechrest et al. Jun 2005 B2
6963980 Mattsson Nov 2005 B1
6968374 Lemieux et al. Nov 2005 B2
6978384 Milliken Dec 2005 B1
7007044 Rafert et al. Feb 2006 B1
7020750 Thiyagaranjan et al. Mar 2006 B2
7035214 Seddigh et al. Apr 2006 B1
7047281 Kausik May 2006 B1
7069342 Biederman Jun 2006 B1
7110407 Khanna Sep 2006 B1
7111005 Wessman Sep 2006 B1
7113962 Kee et al. Sep 2006 B1
7120666 McCanne et al. Oct 2006 B2
7145889 Zhang et al. Dec 2006 B1
7197597 Scheid et al. Mar 2007 B1
7200847 Straube et al. Apr 2007 B2
7215667 Davis May 2007 B1
7242681 Van Bokkelen et al. Jul 2007 B1
7243094 Tabellion et al. Jul 2007 B2
7266645 Garg et al. Sep 2007 B2
7278016 Detrick et al. Oct 2007 B1
7318100 Demmer et al. Jan 2008 B2
7366829 Luttrell et al. Apr 2008 B1
7380006 Srinivas et al. May 2008 B2
7383329 Erickson Jun 2008 B2
7383348 Seki et al. Jun 2008 B2
7388844 Brown et al. Jun 2008 B1
7389357 Duffie, III et al. Jun 2008 B2
7389393 Karr et al. Jun 2008 B1
7417570 Srinivasan et al. Aug 2008 B2
7417991 Crawford et al. Aug 2008 B1
7420992 Fang et al. Sep 2008 B1
7428573 McCanne et al. Sep 2008 B2
7451237 Takekawa et al. Nov 2008 B2
7453379 Plamondon Nov 2008 B2
7454443 Ram et al. Nov 2008 B2
7457315 Smith Nov 2008 B1
7460473 Kodama et al. Dec 2008 B1
7471629 Melpignano Dec 2008 B2
7532134 Samuels et al. May 2009 B2
7555484 Kulkarni et al. Jun 2009 B2
7571343 Xiang et al. Aug 2009 B1
7571344 Hughes et al. Aug 2009 B2
7587401 Yeo et al. Sep 2009 B2
7596802 Border et al. Sep 2009 B2
7619545 Samuels et al. Nov 2009 B2
7620870 Srinivasan et al. Nov 2009 B2
7624446 Wilhelm Nov 2009 B1
7630295 Hughes et al. Dec 2009 B2
7639700 Nabhan et al. Dec 2009 B1
7643426 Lee et al. Jan 2010 B1
7644230 Hughes et al. Jan 2010 B1
7676554 Malmskog et al. Mar 2010 B1
7698431 Hughes Apr 2010 B1
7702843 Chen et al. Apr 2010 B1
7714747 Fallon May 2010 B2
7746781 Xiang Jun 2010 B1
7764606 Ferguson et al. Jul 2010 B1
7827237 Plamondon Nov 2010 B2
7849134 McCanne et al. Dec 2010 B2
7853699 Wu et al. Dec 2010 B2
7873786 Singh et al. Jan 2011 B1
7941606 Pullela et al. May 2011 B1
7945736 Hughes et al. May 2011 B2
7948921 Hughes et al. May 2011 B1
7953869 Demmer et al. May 2011 B2
7970898 Clubb et al. Jun 2011 B2
8069225 McCanne et al. Nov 2011 B2
8072985 Golan et al. Dec 2011 B2
8095774 Hughes et al. Jan 2012 B1
8140757 Singh et al. Mar 2012 B1
8171238 Hughes et al. May 2012 B1
8209334 Doerner Jun 2012 B1
8225072 Hughes et al. Jul 2012 B2
8307115 Hughes Nov 2012 B1
8312226 Hughes Nov 2012 B2
8352608 Keagy et al. Jan 2013 B1
8370583 Hughes Feb 2013 B2
8386797 Danilak Feb 2013 B1
8392684 Hughes Mar 2013 B2
8442052 Hughes May 2013 B1
8447740 Huang et al. May 2013 B1
8473714 Hughes et al. Jun 2013 B2
8489562 Hughes et al. Jul 2013 B1
8565118 Shukla et al. Oct 2013 B2
8595314 Hughes Nov 2013 B1
8613071 Day et al. Dec 2013 B2
8700771 Ramankutty et al. Apr 2014 B1
8706947 Vincent Apr 2014 B1
8725988 Hughes et al. May 2014 B2
8732423 Hughes May 2014 B1
8738865 Hughes et al. May 2014 B1
8743683 Hughes Jun 2014 B1
8755381 Hughes et al. Jun 2014 B2
8811431 Hughes Aug 2014 B2
8885632 Hughes et al. Nov 2014 B2
8929380 Hughes et al. Jan 2015 B1
8929402 Hughes Jan 2015 B1
8930650 Hughes et al. Jan 2015 B1
9036662 Hughes May 2015 B1
9092342 Hughes et al. Jul 2015 B2
9363248 Hughes et al. Jun 2016 B1
20010054084 Kosmynin Dec 2001 A1
20020007413 Garcia-Luna-Aceves et al. Jan 2002 A1
20020040475 Yap et al. Apr 2002 A1
20020061027 Abiru et al. May 2002 A1
20020065998 Buckland May 2002 A1
20020071436 Border et al. Jun 2002 A1
20020078242 Viswanath Jun 2002 A1
20020101822 Ayyagari et al. Aug 2002 A1
20020107988 Jordan Aug 2002 A1
20020116424 Radermacher et al. Aug 2002 A1
20020129260 Benfield et al. Sep 2002 A1
20020131434 Vukovic et al. Sep 2002 A1
20020150041 Reinshmidt et al. Oct 2002 A1
20020163911 Wee et al. Nov 2002 A1
20020169818 Stewart et al. Nov 2002 A1
20020181494 Rhee Dec 2002 A1
20020188871 Noehring et al. Dec 2002 A1
20020194324 Guha Dec 2002 A1
20030002664 Anand Jan 2003 A1
20030009558 Ben-Yehezkel Jan 2003 A1
20030012400 McAuliffe et al. Jan 2003 A1
20030046572 Newman et al. Mar 2003 A1
20030123481 Neale et al. Jul 2003 A1
20030123671 He et al. Jul 2003 A1
20030131079 Neale et al. Jul 2003 A1
20030133568 Stein et al. Jul 2003 A1
20030142658 Ofuji et al. Jul 2003 A1
20030149661 Mitchell et al. Aug 2003 A1
20030149869 Gleichauf Aug 2003 A1
20030214954 Oldak et al. Nov 2003 A1
20030233431 Reddy et al. Dec 2003 A1
20040008711 Lahti et al. Jan 2004 A1
20040047308 Kavanagh et al. Mar 2004 A1
20040083299 Dietz et al. Apr 2004 A1
20040086114 Rarick May 2004 A1
20040088376 McCanne et al. May 2004 A1
20040114569 Naden et al. Jun 2004 A1
20040117571 Chang et al. Jun 2004 A1
20040123139 Aiello et al. Jun 2004 A1
20040179542 Murakami et al. Sep 2004 A1
20040181679 Dettinger et al. Sep 2004 A1
20040199771 Morten et al. Oct 2004 A1
20040202110 Kim Oct 2004 A1
20040203820 Billhartz Oct 2004 A1
20040205332 Bouchard et al. Oct 2004 A1
20040243571 Judd Dec 2004 A1
20040255048 Lev Ran et al. Dec 2004 A1
20050010653 McCanne Jan 2005 A1
20050044270 Grove et al. Feb 2005 A1
20050053094 Cain et al. Mar 2005 A1
20050091234 Hsu et al. Apr 2005 A1
20050111460 Sahita May 2005 A1
20050131939 Douglis et al. Jun 2005 A1
20050132252 Fifer et al. Jun 2005 A1
20050141425 Foulds Jun 2005 A1
20050171937 Hughes et al. Aug 2005 A1
20050177603 Shavit Aug 2005 A1
20050190694 Ben-Nun et al. Sep 2005 A1
20050207443 Kawamura et al. Sep 2005 A1
20050210151 Abdo et al. Sep 2005 A1
20050220019 Melpignano Oct 2005 A1
20050235119 Sechrest et al. Oct 2005 A1
20050243743 Kimura Nov 2005 A1
20050243835 Sharma et al. Nov 2005 A1
20050256972 Cochran et al. Nov 2005 A1
20050278459 Boucher et al. Dec 2005 A1
20050286526 Sood et al. Dec 2005 A1
20060013210 Bordogna et al. Jan 2006 A1
20060026425 Douceur et al. Feb 2006 A1
20060031936 Nelson et al. Feb 2006 A1
20060036901 Yang et al. Feb 2006 A1
20060039354 Rao et al. Feb 2006 A1
20060059171 Borthakur et al. Mar 2006 A1
20060059173 Hirsch et al. Mar 2006 A1
20060117385 Mester et al. Jun 2006 A1
20060143497 Zohar et al. Jun 2006 A1
20060195547 Sundarrajan et al. Aug 2006 A1
20060195840 Sundarrajan et al. Aug 2006 A1
20060212426 Shakara et al. Sep 2006 A1
20060218390 Loughran et al. Sep 2006 A1
20060227717 van den Berg et al. Oct 2006 A1
20060250965 Irwin Nov 2006 A1
20060268932 Singh et al. Nov 2006 A1
20060280205 Cho Dec 2006 A1
20070002804 Xiong et al. Jan 2007 A1
20070011424 Sharma et al. Jan 2007 A1
20070038815 Hughes Feb 2007 A1
20070038816 Hughes et al. Feb 2007 A1
20070038858 Hughes Feb 2007 A1
20070050475 Hughes Mar 2007 A1
20070076693 Krishnaswamy Apr 2007 A1
20070097874 Hughes et al. May 2007 A1
20070110046 Farrell et al. May 2007 A1
20070115812 Hughes May 2007 A1
20070127372 Khan et al. Jun 2007 A1
20070130114 Li et al. Jun 2007 A1
20070140129 Bauer et al. Jun 2007 A1
20070174428 Lev Ran et al. Jul 2007 A1
20070195702 Yuen et al. Aug 2007 A1
20070198523 Hayim Aug 2007 A1
20070226320 Hager et al. Sep 2007 A1
20070244987 Pedersen et al. Oct 2007 A1
20070245079 Bhattacharjee et al. Oct 2007 A1
20070248084 Whitehead Oct 2007 A1
20070258468 Bennett Nov 2007 A1
20070263554 Finn Nov 2007 A1
20070276983 Zohar et al. Nov 2007 A1
20070280245 Rosberg Dec 2007 A1
20080005156 Edwards et al. Jan 2008 A1
20080013532 Garner et al. Jan 2008 A1
20080016301 Chen Jan 2008 A1
20080028467 Kommareddy et al. Jan 2008 A1
20080031149 Hughes et al. Feb 2008 A1
20080031240 Hughes et al. Feb 2008 A1
20080095060 Yao Apr 2008 A1
20080133536 Bjorner et al. Jun 2008 A1
20080133561 Dubnicki et al. Jun 2008 A1
20080184081 Hama et al. Jul 2008 A1
20080205445 Kumar et al. Aug 2008 A1
20080229137 Samuels et al. Sep 2008 A1
20080243992 Jardetzky et al. Oct 2008 A1
20080267217 Colville et al. Oct 2008 A1
20080313318 Vermeulen et al. Dec 2008 A1
20080320151 McCanne et al. Dec 2008 A1
20090024763 Stepin et al. Jan 2009 A1
20090060198 Little Mar 2009 A1
20090063696 Wang et al. Mar 2009 A1
20090080460 Kronewitter, III et al. Mar 2009 A1
20090092137 Haigh et al. Apr 2009 A1
20090100483 McDowell Apr 2009 A1
20090158417 Khanna et al. Jun 2009 A1
20090175172 Prytz et al. Jul 2009 A1
20090234966 Samuels et al. Sep 2009 A1
20090265707 Goodman et al. Oct 2009 A1
20090274294 Itani Nov 2009 A1
20090279550 Romrell et al. Nov 2009 A1
20090281984 Black Nov 2009 A1
20100005222 Brant et al. Jan 2010 A1
20100011125 Yang et al. Jan 2010 A1
20100020693 Thakur Jan 2010 A1
20100054142 Moiso et al. Mar 2010 A1
20100070605 Hughes et al. Mar 2010 A1
20100077251 Liu et al. Mar 2010 A1
20100085964 Weir et al. Apr 2010 A1
20100115137 Kim et al. May 2010 A1
20100121957 Roy et al. May 2010 A1
20100124239 Hughes May 2010 A1
20100131957 Kami May 2010 A1
20100225658 Coleman Sep 2010 A1
20100246584 Ferguson et al. Sep 2010 A1
20100290364 Black Nov 2010 A1
20100318892 Teevan et al. Dec 2010 A1
20110002346 Wu Jan 2011 A1
20110022812 van der Linden et al. Jan 2011 A1
20110113472 Fung et al. May 2011 A1
20110154329 Arcese et al. Jun 2011 A1
20110219181 Hughes et al. Sep 2011 A1
20110276963 Wu et al. Nov 2011 A1
20110299537 Saraiya et al. Dec 2011 A1
20120036325 Mashtizadeh et al. Feb 2012 A1
20120173759 Agarwal et al. Jul 2012 A1
20120221611 Watanabe et al. Aug 2012 A1
20120239872 Hughes et al. Sep 2012 A1
20130018765 Fork et al. Jan 2013 A1
20130044751 Casado et al. Feb 2013 A1
20130080619 Assuncao et al. Mar 2013 A1
20130086236 Baucke et al. Apr 2013 A1
20130094501 Hughes Apr 2013 A1
20130117494 Hughes et al. May 2013 A1
20130121209 Padmanabhan et al. May 2013 A1
20130250951 Koganti Sep 2013 A1
20130263125 Shamsee et al. Oct 2013 A1
20130282970 Hughes et al. Oct 2013 A1
20130343191 Kim et al. Dec 2013 A1
20140052864 Van Der Linden et al. Feb 2014 A1
20140123213 Vank et al. May 2014 A1
20140181381 Hughes et al. Jun 2014 A1
20140379937 Hughes et al. Dec 2014 A1
20150074291 Hughes Mar 2015 A1
20150074361 Hughes et al. Mar 2015 A1
20150078397 Hughes et al. Mar 2015 A1
Foreign Referenced Citations (3)
Number Date Country
1507353 Feb 2005 EP
H05-061964 Mar 1993 JP
WO 2001035226 May 2001 WO
Non-Patent Literature Citations (39)
Entry
Business Wire, “Silver Peak Systems Delivers Family of Appliances for Enterprise-Wide Centralization of Branch Office Infrastructure; Innovative Local Instance Networking Approach Overcomes Traditional Application Acceleration Pitfalls,” Sep. 19, 2005, (available at http://www.businesswire.com/news/home/20050919005450/en/Silver-Peak-Syste- ms-Delivers-Family-Appliances-Enterprise-Wide#.UVzkPk7u-1 (last visited Aug. 8, 2014)).
Riverbed, “Riverbed Introduces Market-Leading WDS Solutions for Disaster Recovery and Business Application Acceleration,” Oct. 22, 2007 (available at http://www.riverbed.com/about/news-articles/pressreleases/riverbed-introd- uces-market-leading-wds-solutions-fordisaster-recovery-and-business-applic- ation-acceleration.html (last visited Aug. 8, 2014).
Tseng, Josh, “When accelerating secure traffic is not secure,” Aug. 27, 2008, (available at http://www.riverbed.com/blogs/whenaccelerati.html?&isSearch=true&pageS- ize=3&page=2 (last visited Aug. 8, 2014)).
Riverbed, “The Riverbed Optimization System (RiOS) v4.0: A Technical Overview,” (explaining “Data Security” through segmentation) (available at http://mediacms.riverbed.com/documents/TechOverview-Riverbed-RiOS.sub.--4- .sub.--0.pdf (last visited Aug. 8, 2014)).
Riverbed, “Riverbed Awarded Patent on Core WDS Technology” (available at: http://www.riverbed.com/about/news-articles/pressreleases/riverbed-awarde- d-patent-on-core-wds-technology.html (last visited Aug. 8, 2014)).
Final Written Decision, dated Dec. 30, 2014, Inter Partes Review Case No. IPR2013-00403.
Final Written Decision, dated Dec. 30, 2014, Inter Partes Review Case No. IPR2013-00402.
Cisco Systems, Inc., “IPsec Anti-Replay Window: Expanding and Disabling,” Cisco IOS Security Configuration Guide. 2005-2006 Last updated: Sep. 12, 2006, 14 pages.
Singh, B., et al., “Future of Internet Security—Ipsec,” Jan. 26, 2005, [online] [Retrieved on Feb. 1, 2005] Retrieved from the Internet <URL: http://www.securitydocs.com/library/2926>.
Muthitacharoen, A., et al., “A Low-bandwidth Network File System,” Oct. 2001, In the Proceedings of the 18th ACM Symposium on Operating Systems Principles, Chateau Lake Louise, Banff, Canada, pp. 174-187.
“Shared LAN Cache Datasheet,” 1996, [online] [Retrieved on Aug. 26, 2009] Retrieved from the Internet <URL:http://www.lancache.com/slcdata.htm>.
Spring et al., “A protocol-independent technique for eliminating redundant network traffic”, ACM SIGCOMM Computer Communication Review, vol. 30, Issue 4 (Oct. 2000) pp. 87-95, Year of Publication: 2000.
Hong, B., et al. “Duplicate data elimination in a SAN file system,” In Proceedings of the 21st Symposium on Mass Storage Systems (MSS '04), Goddard, MD, Apr. 2004. IEEE.
You, L. L. and Karamanolis, C. 2004. “Evaluation of efficient archival storage techniques”, In Proceedings of the 21st IEEE Symposium on Mass Storage Systems and Technologies (MSST).
Douglis, F. et al., “Application specific Delta-encoding via Resemblance Detection,” Published in the 2003 USENIX Annual Technical Conference, 14 Pages.
You, L. L., et al., “Deep Store an Archival Storage System Architecture,” Data Engineering, 2005, Proceedings of the 21st Intl. Conf. on Data Eng.,Tokyo, Japan, Apr. 5-8, 2005, 12 Pages.
Manber, U., “Finding Similar Files in a Large File System,” TR 93-33, Oct. 1994, Department of Computer Science, University of Arizona. <http://webglimpse.net/pubs/TR93-33.pdf>. Also appears in the 1994 winter USENIX Technical Conference.
Knutsson, B., et al., “Transparent Proxy Signalling,” Journal of Communications and Networks, 2001, pp. 164-174, vol. 3, No. 2.
Definition memory (n), Webster's Third New International Dictionary, Unabridged (1993), available at <http://lionreference.chadwyck.com> (Dictionaries/Webster's Dictionary).
Definition appliance, 2c, Webster's Third New International Dictionary, Unabridged (1993), available at <http://lionreference.chadwyck.com> (Dictionaries/Webster's Dictionary).
Newton, H., “Newton's Telecom Dictionary”, 17th Ed., 2001, pp. 38, 201, and 714.
Silver Peak Systems, “The Benefits of Byte-level WAN Deduplication,” 2008.
Final Written Decision, dated Jun. 9, 2015, Inter Partes Review Case No. IPR2014-00245.
Decision Granting Joint Motion to Terminate, Riverbed Technology, Inc. v. Silver Peak Systems, Inc., Case IPR2014-00245, U.S. Pat. No. 8,392,684, Feb. 7, 2018, 4 pages.
Declaration of Frank Fritsch, Riverbed Technology, Inc. v. Silver Peak Systems, Inc., Case IPR2014-00245, U.S. Pat. No. 8,392,684, Nov. 19, 2014, 17 pages.
1st Declaration of Dr. Geoff Kuenning, Riverbed Technology, Inc. v. Silver Peak Systems, Inc., Case IPR2014-00245, U.S. Pat. No. 8,392,684, Aug. 7, 2014, 42 pages.
2nd Declaration of Dr. Geoff Kuenning, Riverbed Technology, Inc. v. Silver Peak Systems, Inc., Case IPR2014-00245, U.S. Pat. No. 8,392,684, Nov. 19, 2014, 32 pages.
A Riverbed Technology, Inc. White Paper: Security and the Riverbed Steelhead Data Store, Riverbed Technology, Inc. v. Silver Peak Systems, Inc., Case IPR2014-00245, Apr. 11, 2005, 6 pages.
The Tolly Group Report: Certeon, Inc., S-Series™ Acceleration Appliance, Riverbed Technology, Inc. v. Silver Peak Systems, Inc., Case IPR2014-00245, Feb. 2006, 8 pages.
Declaration of Steven W. Landauer, Riverbed Technology, Inc. v. Silver Peak Systems, Inc., Case IPR2014-00245, U.S. Pat. No. 8,392,684, Dec. 10, 2013, 96 pages.
Record of Oral Hearing, Riverbed Technology, Inc. v. Silver Peak Systems, Inc., Case IPR2014-00245, U.S. Pat. No. 8,392,684, May 12, 2015, 81 pages.
Patent Owner's Reply in Support of Its Motion to Amend, Riverbed Technology, Inc. v. Silver Peak Systems, Inc., Case IPR2014-00245, U.S. Pat. No. 8,392,684, Nov. 19, 2014, 9 pages.
Petitioner Riverbed Technology, LLC's Opposition to Patent Owner's Motion to Amend, Riverbed Technology, Inc. v. Silver Peak Systems, Inc., Case IPR2014-00245, U.S. Pat. No. 8,392,684, Oct. 14, 2014, 20 pages.
Patent Owner's Motion to Amend Under 37 CFR § 42.121, Riverbed Technology, Inc. v. Silver Peak Systems, Inc., Case IPR2014-00245, U.S. Pat. No. 8,392,684, Aug. 7, 2014, 19 pages.
Opening Brief of Appellant Silver Peak Systems, Inc., Silver Peak Systems, Inc. v. Riverbed Technology, Inc., Appeal No. 15-2072, Case IPR2014-00245, Nov. 24, 2015, 143 pages.
Brief for Intervenor—Director of the United States Patent and Trademark Office, Document: 24, In Re: Silver Peak Systems, Inc., Appeal No. 2015-2072, Case IPR2014-00245, Feb. 8, 2016, 59 pages.
Brief for Intervenor—Director of the United States Patent and Trademark Office, Document: 25, in Re: Silver Peak Systems, Inc., Appeal No. 2015-2072, Case IPR2014-00245, Feb. 8, 2016, 59 pages.
Reply Brief of Appellant Silver Peak Systems, Inc., Appeal No. 15-2072, Case IPR2014-00245, In re: Silver Peak Systems, Inc., Mar. 10, 2016, 33 pages.
United States Court of Appeals for the Federal Circuit, Notice of Entry of Judgment Accompanied by Opinion, Case 15-2042, Oct. 24, 2017, 5 pages.
Continuations (3)
Number Date Country
Parent 14248167 Apr 2014 US
Child 15148671 US
Parent 13757548 Feb 2013 US
Child 14248167 US
Parent 11497026 Jul 2006 US
Child 13757548 US
Continuation in Parts (1)
Number Date Country
Parent 11202697 Aug 2005 US
Child 11497026 US