DATA DISTRIBUTION UTILIZING UNIQUE READ PARAMETERS IN A DISPERSED STORAGE SYSTEM

• US 20110107184A1
• Filed: 07/23/2010
• Published: 05/05/2011
• Est. Priority Date: 10/29/2009
• Status: Active Grant

• Current Assignee: Pure Storage, Inc.
• Original Assignee: Cleversafe Incorporated (International Business Machines Corporation)
• Inventors: GRUBE, GARY W., MARKISON, TIMOTHY W.
• Granted Patent: US 8,433,978 B2
• Time in Patent Office: Days
• US Class Current: 714/768
• CPC Class Codes: G06F 11/1008 in individual solid state devices G06F11/1004 takes precedence
• CPC Class Codes: G06F 11/1076 Parity data used in redundant arrays of independent storages, e.g. in RAID systems
• CPC Class Codes: G06F 11/1092 Rebuilding, e.g. when physically replacing a failing disk
• CPC Class Codes: G11C 29/52 Protection of memory contents; Detection of errors in memory contents
• CPC Class Codes: H03M 13/09 Error detection only, e.g. using cyclic redundancy check [CRC] codes or single parity bit
• CPC Class Codes: H03M 13/15 Cyclic codes, i.e. cyclic shifts of codewords produce other codewords, e.g. codes defined by a generator polynomial, Bose-Chaudhuri-Hocquenghem [BCH] codes H03M13/17 takes precedence
• CPC Class Codes: H03M 13/1515 Reed-Solomon codes
• CPC Class Codes: H03M 13/23 using convolutional codes, e.g. unit memory codes
• CPC Class Codes: H03M 13/356 Unequal error protection [UEP]
• CPC Class Codes: H04N 21/2181 comprising remotely distributed storage units, e.g. when movies are replicated over a plurality of video servers distributed storage of data in networks, e.g. transport arrangements for network file system [NFS], storage area networks [SAN] or network attached storage [NAS], H04L67/1097
• CPC Class Codes: H04N 21/23439 for generating different versions
• CPC Class Codes: H04N 21/2393 involving handling client requests scheduling or organising the servicing of application requests H04L67/60
• CPC Class Codes: H04N 21/274 Storing end-user multimedia data in response to end-user request , e.g. network recorder
• CPC Class Codes: H04N 21/2747 Remote storage of video programs received via the downstream path, e.g. from the server
• CPC Class Codes: H04N 21/6587 Control parameters, e.g. trick play commands, viewpoint selection

Abstract

A method begins by a processing module receiving a plurality of requests to record a broadcast of data. The method continues with the processing module encoding the data using an error coding dispersal storage function to produce a plurality of sets of encoded data slices when the data is broadcast and in response to a request of the plurality of requests. The method continues with the processing module generating a unique retrieval matrix for each of the plurality of requests based on an identity of a requesting device and the error coding dispersal storage function to produce a plurality of unique retrieval matrixes. The method continues with the processing module storing the plurality of sets of encoded data slices and the plurality of unique retrieval matrixes in a dispersed storage network memory as a plurality of unique copies of the data.

Claims

1. A method for execution by a dispersed storage processing module, the method comprises:

receiving a plurality of requests to record a broadcast of data;

encoding the data using an error coding dispersal storage function to produce a plurality of sets of encoded data slices when the data is broadcast and in response to a request of the plurality of requests;

generating a unique retrieval matrix for each of the plurality of requests based on an identity of a requesting device and the error coding dispersal storage function to produce a plurality of unique retrieval matrixes; and

storing the plurality of sets of encoded data slices and the plurality of unique retrieval matrixes in a dispersed storage network (DSN) memory as a plurality of unique copies of the data.

2. The method of claim 1, wherein the plurality of unique retrieval matrixes comprises:

a plurality of collectives of pillar identifiers, wherein each collective includes pillar identifiers corresponding to at least one of the plurality of sets of encoded data slices for retrieving corresponding encoded data slices.

3. The method of claim 1, wherein the generating the unique retrieval matrix is further based on at least one of:

a data identifier;

a unique retrieval matrix associated with at least one other requesting device;

a unique retrieval matrix not associated with any other requesting device; and

a unique retrieval matrix functionality indicator.

4. The method of claim 1, wherein the unique retrieval matrix comprises one or more of:

a pillars list;

a segmenting protocol;

a pre-slice data manipulation function;

a forward error correction encoding function;

a slicing pillar width;

a post-slice data manipulation function;

a write threshold; and

a read threshold.

5. The method of claim 4, wherein the pillars list comprises one of:

at least one collective of pillar identifiers associated with less than a slicing pillar width number and at least the read threshold number of a plurality of dispersed storage (DS) units associated with the DSN memory; and

at least one collective of pillar identifiers associated with less than the slicing pillar width number and at least the read threshold number of the plurality of DS units, wherein the at least one collective of pillar identifiers is unique as compared to every other collective of pillar identifiers associated with previously determined unique retrieval matrixes for the same set of the plurality of sets of encoded data slices.

6. A method for execution by a dispersed storage processing module, the method comprises:

receiving a plurality of playback requests for data from a plurality of requesting devices, wherein the data is encoded via an error coding dispersal storage function to produce a plurality of sets of encoded data slices which are stored in a dispersed storage network (DSN) memory;

obtaining a plurality of unique retrieval matrixes based on identities of the plurality of requesting devices; and

retrieving, from the DSN memory, a plurality of unique copies of the plurality of sets of encoded data slices in accordance with the plurality of unique retrieval matrixes.

7. The method of claim 6, wherein the obtaining the plurality of unique retrieval matrixes further comprises one of:

retrieving the plurality of unique retrieval matrixes from the DSN memory based on the identities of the plurality of requesting devices; and

generating a unique retrieval matrix for each of the plurality of playback requests based on one or more of;

the identities of the plurality of requesting devices;

the error coding dispersal storage function;

a data identifier;

a unique retrieval matrix associated with at least one other requesting device; and

a unique retrieval matrix functionality indicator.

8. The method of claim 6 further comprises:

decoding a unique copy of the plurality of unique copies of the plurality of sets of encoded data slices in accordance with the error coding dispersal storage function to produce a unique copy of the data; and

outputting the unique copy of the data to a corresponding requesting device.

9. The method of claim 6 further comprises:

outputting a unique copy of the plurality of unique copies of the plurality of sets of encoded data slices to a corresponding requesting device.

10. The method of claim 6, wherein the unique retrieval matrix comprises one or more of:

a pillars list;

a segmenting protocol;

a pre-slice data manipulation function;

a forward error correction encoding function;

a slicing pillar width;

a post-slice data manipulation function;

a write threshold; and

a read threshold.

11. The method of claim 10, wherein the pillars list comprises one of:

at least one collective of pillar identifiers associated with less than a slicing pillar width number and at least the read threshold number of a plurality of dispersed storage (DS) units associated with the DSN memory; and

at least one collective of pillar identifiers associated with less than the slicing pillar width number and at least the read threshold number of the plurality of DS units, wherein the at least one collective of pillar identifiers is unique as compared to every other collective of pillar identifiers associated with previously determined unique retrieval matrixes for the same set of the plurality of sets of encoded data slices.

12. A computer comprises:

an interface; and

a processing module operable to;

receive, via the interface, a plurality of requests to record a broadcast of data;

encode the data using an error coding dispersal storage function to produce a plurality of sets of encoded data slices when the data is broadcast and in response to a request of the plurality of requests;

generate a unique retrieval matrix for each of the plurality of requests based on an identity of a requesting device and the error coding dispersal storage function to produce a plurality of unique retrieval matrixes; and

store, via the interface, the plurality of sets of encoded data slices and the plurality of unique retrieval matrixes in a dispersed storage network (DSN) memory as a plurality of unique copies of the data.

13. The computer of claim 12, wherein the plurality of unique retrieval matrixes comprises:

a plurality of collectives of pillar identifiers, wherein each collective includes pillar identifiers corresponding to at least one of the plurality of sets of encoded data slices for retrieving corresponding encoded data slices.

14. The computer of claim 12, wherein the processing module further functions to generate the unique retrieval matrix based on at least one of:

a data identifier;

a unique retrieval matrix associated with at least one other requesting device;

a unique retrieval matrix not associated with any other requesting device; and

a unique retrieval matrix functionality indicator.

15. The computer of claim 12, wherein the unique retrieval matrix comprises one or more of:

a pillars list;

a segmenting protocol;

a pre-slice data manipulation function;

a forward error correction encoding function;

a slicing pillar width;

a post-slice data manipulation function;

a write threshold; and

a read threshold.

16. The computer of claim 15, wherein the pillars list comprises one of:

at least one collective of pillar identifiers associated with less than a slicing pillar width number and at least the read threshold number of a plurality of dispersed storage (DS) units associated with the DSN memory; and

at least one collective of pillar identifiers associated with less than the slicing pillar width number and at least the read threshold number of the plurality of DS units, wherein the at least one collective of pillar identifiers is unique as compared to every other collective of pillar identifiers associated with previously determined unique retrieval matrixes for the same set of the plurality of sets of encoded data slices.

17. A computer comprises:

an interface; and

a processing module operable to;

receive, via the interface, a plurality of playback requests for data from a plurality of requesting devices, wherein the data is encoded via an error coding dispersal storage function to produce a plurality of sets of encoded data slices which are stored in a dispersed storage network (DSN) memory;

obtain a plurality of unique retrieval matrixes based on identities of the plurality of requesting devices; and

retrieve, via the interface, from the DSN memory, a plurality of unique copies of the plurality of sets of encoded data slices in accordance with the plurality of unique retrieval matrixes.

18. The computer of claim 17, wherein the processing module further functions to obtain the plurality of unique retrieval matrixes by one of:

retrieving, via the interface, the plurality of unique retrieval matrixes from the DSN memory based on the identities of the plurality of requesting devices; and

generating a unique retrieval matrix for each of the plurality of playback requests based on one or more of;

the identities of the plurality of requesting devices;

the error coding dispersal storage function;

a data identifier;

a unique retrieval matrix associated with at least one other requesting device; and

a unique retrieval matrix functionality indicator.

19. The computer of claim 17, wherein the processing module further functions to:

decode a unique copy of the plurality of unique copies of the plurality of sets of encoded data slices in accordance with the error coding dispersal storage function to produce a unique copy of the data; and

output, via the interface, the unique copy of the data to a corresponding requesting device.

20. The computer of claim 17, wherein the processing module further functions to:

output, via the interface, a unique copy of the plurality of unique copies of the plurality of sets of encoded data slices to a corresponding requesting device.

21. The computer of claim 17, wherein the unique retrieval matrix comprises one or more of:

a pillars list;

a segmenting protocol;

a pre-slice data manipulation function;

a forward error correction encoding function;

a slicing pillar width;

a post-slice data manipulation function;

a write threshold; and

a read threshold.

22. The computer of claim 21, wherein the pillars list comprises one of:

at least one collective of pillar identifiers associated with less than a slicing pillar width number and at least the read threshold number of a plurality of dispersed storage (DS) units associated with the DSN memory; and

at least one collective of pillar identifiers associated with less than the slicing pillar width number and at least the read threshold number of the plurality of DS units, wherein the at least one collective of pillar identifiers is unique as compared to every other collective of pillar identifiers associated with previously determined unique retrieval matrixes for the same set of the plurality of sets of encoded data slices.