Abstract: A method includes receiving information about a plurality of data chunks and determining if one or more of a plurality of back-end nodes already stores more than a threshold amount of the plurality of data chunks where one of the plurality of back-end nodes is designated as a sticky node. The method further includes, responsive to determining that none of the plurality of back-end nodes already stores more than a threshold amount of the plurality of data chunks, deduplicating the plurality of data chunks against the back-end node designated as the sticky node. Finally, the method includes, responsive to an amount of data being processed, designating a different back-end node as the sticky node.

Abstract: Embodiments of the present invention relate to a system and method of document retention with policy-controlled deletion. Embodiments of the present invention comprise committing to a plurality of documents, deleting one of the plurality of documents, and providing a proof of authorized deletion of the one of the plurality of documents in response to an audit request.

Abstract: A sequence of hashes is received. Each hash corresponds to a data chunk of data to be deduplicated. Locations of previously stored copies of the data chunks are determined, the locations determined based on the hashes. A breakpoint in the sequence of data chunks is determined based on the locations, the breakpoint forming a boundary of a segment of data chunks.

Abstract: A non-transitory computer-readable storage device includes instructions that, when executed, cause one or more processors to receive a sequence of hashes. Next, the one or more processors are further caused to determine locations of previously stored copies of a subset of the data chunks corresponding to the hashes. The one or more processors are further caused to group hashes and corresponding data chunks into segments based in part on the determined information. The one or more processors are caused to choose, for each segment, a store to deduplicate that segment against. Finally, the one or more processors are further caused to combine two or more segments chosen to be deduplicated against the same store and deduplicate them as a whole using a second index.

Abstract: A method includes receiving information about a plurality of data chunks and determining if one or more of a plurality of back-end nodes already stores more than a threshold amount of the plurality of data chunks where one of the plurality of back-end nodes is designated as a sticky node. The method further includes, responsive to determining that none of the plurality of back-end nodes already stores more than a threshold amount of the plurality of data chunks, deduplicating the plurality of data chunks against the back-end node designated as the sticky node. Finally, the method includes, responsive to an amount of data being processed, designating a different back-end node as the sticky node.

Abstract: An apparatus and method convert user behavior data into rewards. The method and apparatus determine an undiluted reward for a user of a population of users. The method and apparatus divide the population of users into groups. The apparatus and method determine a dilution factor for each of the groups and assign and/or transmit a reward to the user based upon the undiluted reward and the dilution factor for the group to which that user belongs.

Abstract: A method for data deduplication includes receiving a set of hashes derived from a data chunk of a set of input data chunks 310. The method includes sampling the set of hashes 320, using an index indentifying data chunk containers that hold data chunks having a hash in the set of sampled hashes 330, and loading indexes for at least one of the identified data chunk containers 340. The method includes determining which of the hashes correspond to data chunks stored in data chunk containers corresponding to the loaded indexes 350 and deciding which of the set of input data chunks should be stored based at least in part on the determination.

Abstract: One embodiment of the present invention includes a method for routing a data object, comprising a sequence of data units, to a particular component data-storage system, or particular group of component data-storage systems, within a distributed, differential electronic-data storage system by selecting one or more subsequences of data units from the data object, computing a characteristic value from the selected subsequences, computing an index from the characteristic value; and directing the data object to the particular component data-storage system, or to the particular group component data-storage systems, identified by the computed index.

Abstract: A method for data deduplication includes receiving a set of hashes derived from a data chunk of a set of input data chunks 310. The method includes sampling the set of hashes 320, using an index indentifying data chunk containers that hold data chunks having a hash in the set of sampled hashes 330, and loading indexes for at least one of the identified data chunk containers 340. The method includes determining which of the hashes correspond to data chunks stored in data chunk containers corresponding to the loaded indexes 350 and deciding which of the set of input data chunks should be stored based at least in part on the determination.

Abstract: Preventing replay attacks on servers. At least one Bloom filter may be set up in a server for tracking requests received from clients. Identifying data may be generated for each request. The identifying data may be checked against the Bloom filter array. If a match is found, the message may be a replay and may be rejected. If a match is not found, the request identifying data may be added to the Bloom filter and the request may be processed.

Abstract: Chunks are stored in a data store, where respective collections of chunks form respective files. An index that maps digests of chunks to pages containing information to recreate the chunks is provided, where the index is stored in persistent storage.

Abstract: Systems, methods, and other embodiments associated with forensic snapshots are described. One example method includes creating a snapshot of an operational data. The example method may also include creating a hash tree by hashing lowest level data blocks of the snapshot to produce lowest level hashes. Creating a hash tree may also include repeatedly growing the hash tree bottom up by selectively hashing lower level hashes into higher level hashes until a root node is produced. The example method may also include providing a forensic data associated with the hash tree, where the forensic data is used to verify the integrity of the snapshot.

Abstract: A first distribution of cases over a first group of categories is received. A categorizer trained using a search-and-confirm technique classifies the cases into a second group of categories. A second distribution of the cases over the second group of categories is generated using results of the classifying. The first and second distributions are compared to identify differences between the first and second distributions.

Abstract: A network includes multiple segments and bridges interconnecting the segments, with hosts coupled to the segments. The bridges are smart bridges that each perform a host location initialization function. The host location initialization function in one bridge is performed in corporation with all other bridges in the bridged network via an instance through a propagation order spanning tree (POST). The initialization method includes obtaining prior host location information which is at least a partial representation of the host locations in the bridged network before the network topology change, obtaining hints on host location changes resulting from the network topology change, and modifying the prior host location information according to the hints to construct host location information for initialization. Location information for at least a portion of the hosts in the bridged network is preserved or discovered quickly each time when the network topology changes.

Abstract: Chunks are stored in a data store, where respective collections of chunks form respective files. An index that maps digests of chunks to pages containing information to recreate the chunks is provided, where the index is stored in persistent storage.

Abstract: Managing end stations locations in a bridged network includes providing a smart bridge, and performing communications operations using a network flood active port connections table, a network flood reaching table, a best path forwarding table and a best path sourcing table. An end station locations revision manages a host location (HLOC) table. End stations locations revision is invoked upon detection of changes in any end station location. The end stations locations revision exchanges location revision grandparent (LRG), a location revision child (LRC) table and a location revision wavefront distribution protocol. The locations revision passes the location revision request from the smart bridge over a topology of the bridged network. A location revision wavefront starts at the root and, spreads a location revision request for revising the HLOC of the other smart bridges. The wavefront spreads by wavefront protocol.

Abstract: A bridged network and a method for performing bridged network topology acquisition. The bridged network includes network segments and smart bridges having one or more ports. The network segments are interconnected by the smart bridges via the ports. Each of the smart bridges being configured to perform steps to accomplish the network topology acquisition. The method also performs steps to accomplish the network topology acquisition. The steps include an inventory construction that compiles a list of the ports that are connected to each of the network segments. Among the ports that are connected to any of the network segments the inventory construction respecting each port operates cooperatively so as to cause the list respecting each of the ports to converge rapidly to the state in which all the lists are similar and yielding a uniform segment inventory.

Abstract: When a source program containing annotations is processed by a user-selected tool, the annotations in the source program are detected by a lexer and passed to an annotation processor corresponding to the selected tool. The system contains a number of annotation processors and a number of program processing tools, and the annotation processor to which the annotations are passed is selected based upon the user-selected tool. The selected annotation processor converts annotations compatible with the user-selected tool into annotation tokens and returns the annotation tokens to the lexer. The lexer generates tokens based upon the programming-language statements in the source program, and passes both the tokens and annotation tokens to a parser. The parser, in turn, assembles the tokens and annotation tokens into an abstract syntax tree, which is then passed to the user-selected tool for further processing.

Abstract: A computerized method selectively accepts access requests from a client computer connected to a server computer by a network. The server computer receives an access request from the client computer. In response, the server computer generates a predetermined number of random characters. The random characters are used to form a string in the server computer. The string is randomly modified either visually or audibly to form a riddle. The original string becomes the correct answer to the riddle. The server computer renders the riddle on an output device of the client computer. In response, the client computer sends an answer to the server. Hopefully, the answer is a user's guess for the correct answer. The server determines if the guess is the correct answer, and if so, the access request is accepted.