Jeffrey Vincent Tofano

US Patent:

8176292, May 8, 2012

Filed:

Aug 24, 2010

Appl. No.:

12/862712

Inventors:

Jeffrey Vincent Tofano - San Jose CA, US

International Classification:

G06F 12/00

US Classification:

711170, 711206

Abstract:

Example apparatus, methods, and computers control configurable, variable data reduction. One example method includes identifying data reduction controlling attributes in an object to be data reduced by a configurable variable data reducer. The attributes provide information upon which decisions concerning whether and/or how to data reduce the object can be based. The example method also includes controlling a configurable variable data reducer to selectively data reduce the object based, at least in part, on the data reduction controlling attributes. The control exercised can determine whether, where, when, and/or how data reduction will proceed.

US Patent:

8195629, Jun 5, 2012

Filed:

Dec 16, 2010

Appl. No.:

12/970143

Inventors:

Jeffrey Vincent Tofano - San Jose CA, US

International Classification:

G06F 17/30

US Classification:

707694

Abstract:

Example apparatus, methods, and computers control establishing a shared parse scope between two computers that intend to be involved in a shared de-duplication action. One example method includes, upon determining that a first de-duplication logic and a second de-duplication logic are to participate in a shared de-duplication action for an object, controlling the first de-duplication logic to establish a shared parse scope with the second de-duplication logic. Establishing the shared parse scope may include negotiations between the computers, where the negotiations transfer dialect information. The dialect information may take the form of rules. The method may also include persisting the shared parse scope.

US Patent:

8423519, Apr 16, 2013

Filed:

Feb 28, 2011

Appl. No.:

13/036091

Inventors:

Jeffrey Vincent Tofano - San Jose CA, US

International Classification:

G06F 17/30

US Classification:

707692

Abstract:

Example apparatus, methods, data structures, and computers control indexing to facilitate duplicate determinations. One example method includes indexing, in a global index, a unique chunk processed by a data de-duplicator. Indexing the unique chunk in the global index can include updating an expedited data structure associated with the global index. The example method can also include selectively indexing, in a temporal index, a relationship chunk processed by the data de-duplicator. The relationship chunk is a chunk that is related to another chunk processed by the data de-duplicator by sequence, storage location, and/or similarity hash value. Indexing the relationship chunk in the temporal index can also include updating one or more expedited data structures associated with the temporal index. The expedited data structures and indexes can then be consulted to resolve a duplicate determination being made by a data reducer.

US Patent:

8442956, May 14, 2013

Filed:

Jan 16, 2012

Appl. No.:

13/351192

Inventors:

Jeffrey Vincent Tofano - San Jose CA, US

Assignee:

Wells Fargo Capital Finance, LLC - Santa Monica CA

International Classification:

G06F 17/30

US Classification:

707692

Abstract:

Example apparatus, methods, and computers perform sampling based data de-duplication. One example method controls a data de-duplication computer to compute a sampling sequence for a sub-block of data and to use the sampling sequence to locate a stored sub-block known to the data de-duplication computer. Upon finding a stored sub-block to compare to, the method includes controlling the data de-duplication computer to determine a degree of similarity (e. g. , duplicate, very similar, somewhat similar, very dissimilar, completely dissimilar, x % similar) between the sub-block and the stored sub-block and to control whether and how the sub-block is stored and/or transmitted based on the degree of similarity. The degree of similarity can also control whether and how the data de-duplication computer updates a dedupe data structure(s) that stores information for finding groups of similarity sampling sequence related sub-blocks.

US Patent:

8489611, Jul 16, 2013

Filed:

Jul 14, 2011

Appl. No.:

13/182495

Inventors:

Jeffrey Vincent Tofano - San Jose CA, US

International Classification:

G06F 7/00
G06F 17/30

US Classification:

707741, 707747

Abstract:

Example apparatus, methods, and computers control processing delta chunks with delta hashes. One example method includes computing a first hash for a chunk for which a duplicate determination is to be made. The first hash is suitable for making the duplicate chunk determination. The method also includes computing a delta hash for the chunk. The delta hash is suitable for making a delta chunk determination. The method controls a de-duplication logic to process the chunk as a duplicate upon determining that the first hash matches a stored first hash. The method controls the de-duplication logic to process the chunk as a delta chunk upon determining that the first hash does not match a stored first hash and that the delta hash matches a stored delta hash. Processing a chunk as a delta chunk may include storing a reference to a stored chunk and storing delta hash information.

US Patent:

8504595, Aug 6, 2013

Filed:

Dec 7, 2011

Appl. No.:

13/373980

Inventors:

Jeffrey Tofano - San Jose CA, US

International Classification:

G06F 17/30

US Classification:

707813, 707633, 707642, 707662, 707665, 707667

Abstract:

Example methods and apparatus associated with data de-duplication for a global coherent de-duplication repository are provided. In one example a request related to data de-duplication is transmitted to a plurality of nodes associated with the global coherent de-duplication repository. Responses to the request are received from at least a subset of nodes in the plurality of nodes. Affinity scores are assigned to nodes of the subset of nodes based, at least in part, on affinity data from the responses. A node is selected to perform the request related to de-duplication from the subset of nodes of the plurality of nodes based, at least in part, on the affinity score assigned to the nodes.

US Patent:

8543551, Sep 24, 2013

Filed:

Jul 14, 2011

Appl. No.:

13/182498

Inventors:

Jeffrey Vincent Tofano - San Jose CA, US

International Classification:

G06F 7/00
G06F 17/00

US Classification:

707687, 707694, 707698

Abstract:

Example apparatus, methods, and computers participate in collaborative, distributed, data de-duplication. One example method includes initializing a layered parser in a first node in a collaborative distributed data de-duplication (CDDD) topology with a first set of de-duplication control parameters. After transmitting some information to another node in the CDDD topology, the method includes selectively reconfiguring the layered parser in response to feedback acquired from the second node in the CDDD topology. The feedback concerns the data provided by the layered parser.

US Patent:

8572053, Oct 29, 2013

Filed:

Dec 9, 2010

Appl. No.:

12/963914

Inventors:

Jeffrey Vincent Tofano - San Jose CA, US

International Classification:

G06F 17/30

US Classification:

707692

Abstract:

Example apparatus, methods, and computers support data de-duplication indexing. One example apparatus includes a processor, a memory, and an interface to connect the processor, memory, and a set of logics. The set of logics includes an establishment logic to instantiate one-to-many de-duplication data structures, a manipulation logic to update the de-dupe data structure(s), a key logic to generate a key from a block of data to be de-duplicated, and a similarity logic to make a similarity determination for the block. The similarity determination identifies the block as a unique block, a duplicate block, or a block that meets a similarity threshold with respect to a stored de-duplicated block accessible through the dedupe data structure. The similarity determination involves comparing the block to be de-duplicated to a stored block available to the apparatus using a byte-by-byte approach, a hash approach, a delta hash approach and/or a sampling sequence approach.