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Data Compression Algorithms for Energy-Constrained Devices in Delay Tolerant Networks

Data Compression Algorithms for Energy-Constrained Devices in Delay Tolerant Networks. Christopher M. Sadler and Margaret Martonosi In: Proc. of the 4th ACM Conference on Embedded Networked Sensor Systems (SenSys), 2006. Reporter: 王滋農. 1. Motivation.

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Data Compression Algorithms for Energy-Constrained Devices in Delay Tolerant Networks

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  1. Data Compression Algorithms for Energy-Constrained Devices in Delay Tolerant Networks Christopher M. Sadler and Margaret Martonosi In: Proc. of the 4th ACM Conference on Embedded Networked Sensor Systems (SenSys), 2006. Reporter: 王滋農

  2. 1. Motivation • Previous algorithms of compressing acquired data in sensor systems - application-specific algorithms - off-the-shelf algorithms → Not for resource-constrained sensor nodes • Standard compression algorithms are aimed at saving storage not energy

  3. 2. Outline • LZW compression • LZW for Sensor Nodes (S-LZW) • S-LZW with Mini-Cache (S-LZW-MC)

  4. 3.1 LZW introduction (1/4) • The LZW Compression Algorithm is a dictionary-based algorithm, which always tries to output short codes for strings that are already present in it's dictionary • LZW compression uses a code table, with 4096 (12 bits) as a common choice for the number of table entries • Codes 0-255 (ASCII code 8 bits) in the code table are always assigned to represent single bytes from the input file • When encoding begins the code table contains only the first 256 entries, with the remainder of the table being blanks • Compression is achieved by using codes 256 through 4095 to represent sequences of bytes • As the encoding continues, LZW identifies repeated sequences in the data, and adds them to the code table

  5. 3.1 LZW algorithm (2/4) Initialize table with single character strings P = first input character Codeword = 256 WHILE not end of input stream C = next input character IF P + C is in the string table P = P + C ELSE output the code for P add P + C to the string table Codeword++ P = C END IF END WHILE output code for P

  6. 3.1 LZW example (3/4) • Compressing the string: BABAABAAA

  7. 3.1 LZW example (4/4) • Uncompressed String: aaabbbbbbaabaaba Number of bits = Total number of characters * 8 = 16 * 8 = 128 bits • Compressed string (codewords): <97><256><98><258><259><257><261> Number of bits = Total Number of codewords * 12 = 7 * 12 = 84 bits

  8. Outline • LZW compression • LZW for Sensor Nodes(S-LZW) • S-LZW with Mini-Cache (S-LZW-MC)

  9. 3.2 S-LZW introduction (1/5) • Never deliver 100% of data to others - dictionary size - data size

  10. 3.2 S-LZW algorithm (2/5) • Dictionary size - Experimented with 512, 768, 1024 & Unlimited. - Block sizes of 1, 2, 4 & 10 Flash pages. • S‐LZW uses 512 entry dictionary and 4 pages or less

  11. 3.2 S-LZW algorithm (3/5)

  12. 3.2 S-LZW algorithm (4/5) • Data Size – Evaluated 1, 2 & 4 flash page sizes. – Compressed either 2 pages in one block or two individual one‐page blocks. – Also, 4 pages in either one block or two individual two page blocks. – Compression ratio benefits while using a block of 2 pages. SS, GDI, ZNet & Calgeo improvements – 25.5%, 12.9%, 4.6%, 3.3%. – Compute times benefit while using a block of 2 pages. SS, GDI, ZNet & Calgeo improvements – 24.5%, 1.7%, 5.3%, 1.1% • S‐LZW compresses data in block of 528 Bytes (2 Pages) → SS (SensorScope): indoor environmental monitoring → ZNet (ZebraNet): a combination GPS data and debugging data → GDI (Great Duck Island):Habitat and environmental monitoring data → Calgeo (Calgary Corpus): seismic data

  13. … … … 3.2 S-LZW algorithm (5/5) SENSOR DATA – N BYTES GENERATED OVER TIME … 528 B Block (2 Flash Pages) 528 B Block (2 Flash Pages) 528 B Block (2 Flash Pages) … COMP. ALGORITHM COMP. ALGORITHM COMP. ALGORITHM … Compressed Data Compressed Data Compressed Data …

  14. Outline • LZW compression • LZW for Sensor Nodes(S-LZW) • S-LZW with Mini-Cache (S-LZW-MC)

  15. 3.3 S-LZW-MC introduction (1/3) • A variant of S-LZW • Data acquiring over short intervals

  16. Flow chart of S-LZW-MC 3.3 S-LZW-MC flow chart (2/3)

  17. 3.3 S-LZW-MC example (3/3) • Hit => Saves multiple bits: (Log2N)+1 Bit • Miss => Costs just 1 extra escape bit: (9+1)

  18. 4. Novelty • Proposing novel approaches tailored to the unique trade-offs and constraints of sensors

  19. 5. Strength • An efficient and lossless data compression algorithms on the source node • The compression algorithms are suitable for static and mobile sensor network and applicable to a wide range of applications

  20. 6. Weakness • This paper doesn’t clearly describe how to solve the problem when the dictionary fills • Not the optimum compression ratio

  21. Thank you

  22. What happens when the dictionary gets too large (i.e., when all the 4096 locations have been used)? • Here are some options usually implemented: • Simply forget about adding any more entries and use the table as is. • Throw the dictionary away when it reaches a certain size. • Throw the dictionary away when it is no longer effective at compression. • Clear entries 256-4095 and start building the dictionary again. • Some clever schemes rebuild a string table from the last N input characters.

  23. Appendix

  24. LZW Decompression • The LZW decompressor creates the same string table during decompression. • It starts with the first 256 table entries initialized to single characters. • The string table is updated for each character in the input stream, except the first one. • Decoding achieved by reading codes and translating them through the code table being built.

  25. LZW Decompression Algorithm 1 Initialize table with single character strings 2 OLD = first input code 3 output translation of OLD 4 WHILE not end of input stream 5 NEW = next input code 6  IF NEW is not in the string table 7 S = translation of OLD 8   S = S + C 9 ELSE 10  S = translation of NEW 11 output S 12   C = first character of S 13   OLD + C to the string table 14 OLD = NEW 15 END WHILE

  26. Example 2: LZW Decompression 1 Example 2: Use LZW to decompress the output sequence of Example 1: <66><65><256><257><65><260>.

  27. Example 2: LZW Decompression Step 1 <66><65><256><257><65><260> Old = 65 S = A New = 66 C = A

  28. Example 2: LZW Decompression Step 2 <66><65><256><257><65><260> Old = 256 S = BA New = 256 C = B

  29. Example 2: LZW Decompression Step 3 <66><65><256><257><65><260> Old = 257 S = AB New = 257 C = A

  30. Example 2: LZW Decompression Step 4 <66><65><256><257><65><260> Old = 65 S = A New = 65 C = A

  31. Example 2: LZW Decompression Step 5 <66><65><256><257><65><260> Old = 260 S = AA New = 260 C = A

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