DATA SYSTEM FOR INTERFACING WITH A REMOTE DATA STORAGE FACILITY USING COMPRESSIVE SENSING AND ASSOCIATED METHODS

• US 20130151924A1
• Filed: 12/08/2011
• Published: 06/13/2013
• Est. Priority Date: 12/08/2011
• Status: Active Grant

• Current Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Original Assignee: Harris Corporation (L3Harris Technologies, Inc.)
• Inventors: Beadle, Edward R., Zahm, Charles
• Granted Patent: US 8,516,340 B2
• Time in Patent Office: Days
• US Class Current: 714/763
• CPC Class Codes: G06F 21/606 by securing the transmission between two devices or processes
• CPC Class Codes: G06F 21/85 interconnection devices, e.g. bus-connected or in-line devices
• CPC Class Codes: H03M 13/1102 Codes on graphs and decoding on graphs, e.g. low-density parity check [LDPC] codes
• CPC Class Codes: H03M 13/23 using convolutional codes, e.g. unit memory codes
• CPC Class Codes: H03M 13/2957 Turbo codes and decoding
• CPC Class Codes: H04L 1/0057 Block codes H04L1/0061, H04L1/0064 take precedence
• CPC Class Codes: H04L 1/0059 Convolutional codes
• CPC Class Codes: H04L 67/125 involving control of end-device applications over a network
• CPC Class Codes: H04L 69/04 Protocols for data compression, e.g. ROHC

Abstract

A data handling system includes a compressive sensing unit that receives a source date file. A sparseness module compressive sensing unit generates a sparse source data file by inducing sparseness into the source data file. A measurement module within the compressive sensing unit generates a compressed sensed source data file from the sparse source data file and based on a sensing matrix. The compressed sensed source data file is to be transmitted to a remote data storage facility for storage. A recovery unit generates the source data file from the compressed sensed source data file retrieved from the remote data storage facility and based upon the sensing matrix.

Claims

1. A data handling system comprising:

a compressive sensing unit configured to receive a source date file, and comprising

a sparseness module configured to generate a sparse source data file by inducing sparseness into the source data file, and

a measurement module configured to generate a compressed sensed source data file from the sparse source data file and based on a sensing matrix, the compressed sensed source data file configured to be transmitted to a remote data storage facility for storage; and

a recovery unit configured to recover the source data file from the compressed sensed source data file retrieved from the remote data storage facility and based upon the sensing matrix.

2. The data handling system according to claim 1 wherein said recovery unit is further configured to perform a trial recovery of the compressed sensed source data file prior to being transmitted to the remote data storage facility for storage, and if the trial recovery is successful, then perform the transmitting.

3. The data handling system according to claim 2 wherein said measurement module is further configured to re-generate the compressed sensed source data file from the sparse source data file and based on a new sensing matrix if the trial recovery is unsuccessful, and wherein said recovery unit is configured to perform a trial recovery on the re-generated compressed sensed source data file prior to being transmitted.

4. The data handling system according to claim 1 wherein said measurement module is configured to randomly generate the sensing matrix.

5. The data handling system according to claim 4 wherein said measurement module is configured to randomly generate each sensing matrix based on a mapping and a respective seed.

6. The data handling system according to claim 5 wherein said measurement matrix is configured to chaotically generate the respective seed for each sensing matrix.

7. The data handling system according to claim 5 further comprising a memory coupled to said compressive sensing unit and said recovery unit to store the mapping and the seed for each respective sensing matrix;

and wherein said recovery unit is configured to reconstruct the sensing matrix based on the stored mapping and the stored respective seed.

8. The data handling system according to claim 7 wherein said measurement module is configured to store a time stamp in said memory corresponding to when the sensing matrix was generated, with the time stamp being used to identify the respective seed used to generate the sensing matrix;

and wherein said recovery unit is configured to retrieve the respective seed from said memory based on the time stamp associated therewith to reconstruct the sensing matrix.

9. The data handling system according to claim 1 wherein said compressive sensing unit further comprises a data integrity module configured to add authentication symbols to the sparse source data file;

and wherein said recovery unit further comprises an integrity check module configured to authenticate the retrieved compressed sensed data file based on the authentication symbols added by said data integrity module.

10. The data handling system according to claim 1 wherein said compressive sensing unit further comprises a forward error correction (FEC) module configured to add error correction symbols to the sparse source data file;

and wherein said recovery unit further comprises an error detection and correction module configured to correct for errors in the retrieved compressed sensed data file based on the error correction symbols added by said FEC module.

11. The data handling system according to claim 1 wherein said sparseness module is configured to induce sparseness into the source data file based on directed embedding.

12. The data handling system according to claim 1 wherein said sparseness module is configured to induce sparseness into the source data file based on a sparsification transform.

13. A data handling system comprising:

a compressive sensing unit configured to receive a source date file, and comprising

a sparseness module configured to generate a sparse source data file by inducing sparseness into the source data file, and

a measurement module configured to generate a compressed sensed source data file from the sparse source data file and based on a sensing matrix, with the sensing matrix being defined by mapping and a randomly generated seed, and the compressed sensed source data file configured to be transmitted to a remote data storage facility for storage;

a memory coupled to said compressive sensing unit and configured to store the mapping and the respective seed for the sensing matrix; and

a recovery unit coupled to said memory and configured to reconstruct the sensing matrix based on the stored mapping and the stored respective seed, and to recover the source data file from the compressed sensed source data file retrieved from the remote data storage facility and based upon the reconstructed sensing matrix.

14. The data handling system according to claim 13 wherein said recovery unit is further configured to perform a trial recovery of the compressed sensed source data file prior to being transmitted to the remote data storage facility for storage, and if the trial recovery is successful, then perform the transmitting.

15. The data handling system according to claim 14 wherein said measurement module is further configured to re-generate the compressed sensed source data file from the sparse source data file and based on a new sensing matrix if the trial recovery is unsuccessful, and wherein said recovery unit is configured to perform a trial recovery on the re-generated compressed sensed source data file prior to being transmitted.

16. The data handling system according to claim 13 wherein said measurement matrix is configured to chaotically generate the randomly generated seed for each sensing matrix.

17. The data handling system according to claim 13 wherein said measurement module is configured to store a time stamp in said memory corresponding to when the sensing matrix was generated, with the time stamp being used to identify the respective seed used to generate the sensing matrix;

and wherein said recovery unit is configured to retrieve the respective seed from said memory based on the time stamp associated therewith to reconstruct the sensing matrix.

18. The data handling system according to claim 17 wherein said compressive sensing unit further comprises a forward error correction (FEC) module configured to add error correction symbols to the sparse source data file;

and wherein said recovery unit further comprises an error detection and correction module configured to correct for errors in the retrieved compressed sensed data file based on the error correction symbols added by said FEC module.

19. The data handling system according to claim 13 wherein said compressive sensing unit further comprises a data integrity module configured to add authentication symbols to the sparse source data file;

and wherein said recovery unit further comprises an integrity check module configured to authenticate the retrieved compressed sensed data file based on the authentication symbols added by said data integrity module.

20. A method for operating a data handling system comprising:

receiving a source date file;

generating a sparse source data file by inducing sparseness into the source data file;

generating a compressed sensed source data file from the sparse source data file and based on a sensing matrix;

transmitting the compressed sensed source data file to a remote data storage facility for storage;

retrieving the compressed sensed source data file from the remote data storage facility; and

recovering the source data file from the retrieved compressed sensed source data file and based upon the sensing matrix.

21. The method according to claim 20 further comprising performing a trial recovery of the compressed sensed source data file prior to being transmitted to the remote data storage facility for storage, and if the trial recovery is successful, then perform the transmitting.

22. The method according to claim 21 further comprising re-generating the compressed sensed source data file from the sparse source data file and based on a new sensing matrix if the trial recovery is unsuccessful, and further comprising performing a trial recovery on the re-generated compressed sensed source data file prior to being transmitted.

23. The method according to claim 20 comprising randomly generating the sensing matrix.

24. The method according to claim 23 wherein each randomly generated sensing matrix is based on mapping and a respective seed.

25. The method according to claim 24 comprising chaotically generating each respective seed.

26. The method according to claim 24 further comprising storing the mapping and the respective seed for each sensing matrix;

and wherein generating the source data file from the retrieved compressed sensed source data file is based on using the stored mapping and the stored respective seed to reconstruct the sensing matrix.

27. The method according to claim 26 further comprising storing a time stamp corresponding to when the sensing matrix was generated, with the time stamp being used to identify the respective seed used to generate the sensing matrix;

and wherein generating the source data file from the retrieved compressed sensed source data file is further based on retrieving the respective seed from storage based on the time stamp associated therewith to reconstruct the sensing matrix.

28. The method according to claim 20 further comprising:

adding authentication symbols to the sparse source data file before the transmitting; and

authenticating the compressed sensed data file after the retrieving based on the added authentication symbols.

29. The method according to claim 20 further comprising:

adding error correction symbols to the sparse source data file before the transmitting; and

correcting for errors in the compressed sensed data file after the retrieving based on the added error correction symbols.

30. The method according to claim 20 wherein generating the sparse source data file by inducing sparseness into the source data file is based on directed embedding.

31. The method according to claim 20 wherein generating the sparse source data file by inducing sparseness into the source data file is based on a sparsification transform.