ACM Home Page
Please provide us with feedback. Feedback
Energy-aware lossless data compression
Full text PdfPdf (874 KB)
Source ACM Transactions on Computer Systems (TOCS) archive
Volume 24 ,  Issue 3  (August 2006) table of contents
Pages: 250 - 291  
Year of Publication: 2006
ISSN:0734-2071
Authors
Kenneth C. Barr  MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
Krste Asanović  MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 32,   Downloads (12 Months): 294,   Citation Count: 3
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1151690.1151692
What is a DOI?

ABSTRACT

Wireless transmission of a single bit can require over 1000 times more energy than a single computation. It can therefore be beneficial to perform additional computation to reduce the number of bits transmitted. If the energy required to compress data is less than the energy required to send it, there is a net energy savings and an increase in battery life for portable computers. This article presents a study of the energy savings possible by losslessly compressing data prior to transmission. A variety of algorithms were measured on a StrongARM SA-110 processor. This work demonstrates that, with several typical compression algorithms, there is a actually a net energy increase when compression is applied before transmission. Reasons for this increase are explained and suggestions are made to avoid it. One such energy-aware suggestion is asymmetric compression, the use of one compression algorithm on the transmit side and a different algorithm for the receive path. By choosing the lowest-energy compressor and decompressor on the test platform, overall energy to send and receive data can be reduced by 11% compared with a well-chosen symmetric pair, or up to 57% over the default symmetric zlib scheme.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Advanced RISC Machines Ltd. (ARM). 1998. Writing Efficient C for ARM. Application note 34. Go online to www.arm.com/pdfs.
 
2
Agilent Technologies. 2000. Agilent 34401A Multimeter: User's Guide, 5th ed. Palo Alto, CA.
 
3
Austin, T. M. and Burger, D. C. 2001. SimpleScalar version 4.0 release (tutorial). In Proceedings of the 34th Annual International Symposium on Microarchitecture.
 
4
Banerjee, S. and Misra, A. 2004. Power adaptation based optimization for energy efficient reliable wireless paths. Tech. rep. Department of Computer Sciences, University of Wisconsin-Madison, Madison, WI.
 
5
Bell, T. and Kulp, D. 1989. Longest match string searching for Ziv-Lempel compression. Tech. Rep. 06/89. Department of Computer Science, University of Canterbury, Christchurch New Zealand.
 
6
Bell, T., Powell, M., Horlor, J., and Arnold, R. 1997. The Canterbury Corpus. Go online to http://www.corpus.canterbury.ac.nz/.
7
8
 
9
Burger, D. C. and Austin, T. M. 1997. The SimpleScalar tool set, version 2.0. Tech. Rep. CS-TR-97-1342. University of Wisconsin, Madison, Madison, WI.
 
10
Burrows, M. and Wheeler, D. J. 1994. A block-sorting lossless data compression algorithm. Tech. Rep. 124. Digital Systems Research Center, Palo Alto, CA.
 
11
Chang, F., Farkas, K., and Ranganathan, P. 2002. Energy-driven statistical profiling: Detecting software hotspots. In Proceedings of the 2nd Workshop on Power-Aware Computer Systems (HPCA-8).
 
12
Chang, J.-H. and Tassiulas, L. 2000. Energy conserving routing in wireless ad-hoc networks. In Proceedings of IEEE INFOCOM. 22--31.
 
13
Cleary, J. G. and Witten, I. H. 1984. Data compression using adaptive coding and partial string matching. IEEE Trans. Commun. 32, 4 (Apr.), 396--402.
 
14
 
15
 
16
 
17
Flinn, J., Farkas, K. I., and Anderson, J. 2000. Power and energy characterization of the Itsy pocket computer (version 1.5). Tech. Rep. TN-56. Compaq Computer Corporation, Houston, TX.
 
18
 
19
Gailly, J. 1999. Go online to comp.compression Internet newsgroup: Frequently Asked Questions.
 
20
Gailly, J. and Adler, M. 2002. zlib. Go online to http://www.gzip.org/zlib.
 
21
Gilchrist, J. 2002. Archive comparison test. Go online to http://compression.ca.
 
22
Havinga, P. J. 1999. Energy efficiency of error correction on wireless systems. In Proceedings of the IEEE Wireless Communications and Networking Conference.
 
23
Hicks, J. 2005. Director, MIT-Quanta T-Party Project. Personal communication.
 
24
Hicks, J. et al. 1999. Compaq personal server project. Go online to http://crl.research.compaq.com/projects/personalserver/default.htm.
25
26
 
27
 
28
IBM. 2001. IBM J. Res. Devel. 45, 2. Preface by Richard E. Harper, Guest Editor.
 
29
Intel Corporation. 2000. SA-110 Microprocessor Technical Reference Manual. Intel Corporation, Santa Clara, CA.
 
30
Intel Corporation. 2001. Intel StrongARM SA-1110 Microprocessor Developer's Manual. Intel Corporation, Santa Clara, CA.
 
31
 
32
Jamieson, K. 2002. Implementation of a power-saving protocol for ad hoc wireless networks. M.S. thesis. Massachusetts Institute of Technology, Cambridge, MA.
 
33
Jannesen, P. et. al 1996. (n)compress. Available, among other places, in Redhat 7.2 distribution of Linux.
 
34
Jung, B. and Burleson, W. P. 1994. A VLSI systolic array architecture for Lempel-Ziv based data compression. In Proceedings of the International Symposium on Circuits and Systems.
 
35
 
36
Krashinsky, R. 2003. Efficient Web browsing for mobile clients using HTTP compression. Tech. Rep. MIT-LCS-TR-882. MIT Laboratory for Computer Science, Combridge, MA.
37
38
39
 
40
Lycos. 2002. Lycos 50. Top 50 searches on Lycos for the week ending September 21, 2002.
 
41
McEliece, R. 1977. The theory of information and coding. In Encyclopedia of Mathematics and Its Application. Vol. 3. Addison-Wesley, Reading, MA.
42
 
43
Mogul, J. C. 1999. Trace-based analysis of duplicate suppression in HTTP. Tech. Rep. 99.2. Compaq Computer Corporation, Houston, TX.
 
44
Mogul, J. C., Douglis, F., Feldmann, A., and Krishnamurthy, B. 1997. Potential benefits of delta encoding and data compression for HTTP. Tech. Rep. 97/4a. Compaq Computer Corporation, Houston, TX.
 
45
Montanaro et al., J. 1996. A 160-MHz, 32-b, 0.5-W CMOS RISC microprocessor. IEEE J. Sol.-State Circ. 31, 11 (Nov.), 1703--1714.
 
46
47
 
48
Nathuji, R. 2000. Characterization of DRAM. MIT Advanced Undergraduate Project. Massachusetts Institute of Technology, Cambridge, MA.
 
49
Nielsen NetRatings Audience Measurement Service. 2002. Top 25 U.S Properties; Week of Sept. 15th. Go online to www.nielsen-netratings.com.
 
50
 
51
Oberhumer, M. F. 2000. Lzo. Go on line to http://www.oberhumer.com/opensource/lzo/.
 
52
 
53
Santos, J. and Wetherall, D. 1998. Increasing effective link bandwidth by suppressing replicated data. In Proceedings of the USENIX Annual Technical Conference. 213--224.
 
54
 
55
Seward, J. 1999. bzip2. Go online to http://www.spec.org/osg/cpu2000/CINT2000/256.bzip2/docs/256.bzip2.html.
 
56
Seward, J. 2000. e2comp bzip2 library. Go online to http://cvs.bofh.asn.au/e2compr/ index.html.
 
57
 
58
Shannon, C. E. 1948. A mathematical theory of communication. Bell Syst. Tech. J. 27, 379--423 and 623--656.
 
59
 
60
Shkarin, D. 2002b. PPMd. Go online to ftp://ftp.elf.stuba.sk/pub/pc/pack/ppmdi1.rar.
61
 
62
63
64
 
65
Standard Performance Evaluation Corporation. 2000. CPU2000. Go online to www.spec.org.
 
66
Taylor, C. N. and Dey, S. 2001. Adaptive image compression for wireless multimedia communication. In Proceedings of the IEEE International Conference on Communication.
 
67
 
68
Tridgell, A. 2000. Efficient algorithms for sorting and synchronization. Ph.D. dissertation. Australian National University, Canberra, Australia.
 
69
Viredaz, M. A. and Wallach, D. A. 2000. Power evaluation of Itsy version 2.3. Tech. Rep. TN-57. Compaq Computer Corporation, Houston, TX.
 
70
Viredaz, M. A. and Wallach, D. A. 2001. Power evaluation of Itsy version 2.4. Tech. Rep. TN-59. Compaq Computer Corporation, Houston, TX.
 
71
Welch, T. A. 1984. A technique for high-performance data compression. IEEE Comput. 17, 6, 8--19.
72
 
73
Yang, H., Gao, G. R., Marquez, A., Cai, G., and Hu, Z. 2001. Power and energy impact of loop transformations. In Proceedings of the Workshop on Compilers and Operating Systems for Low Power 2001, Parallel Architecture and Compilation Techniques.
 
74
Ziv, J. and Lempel, A. 1977. A universal algorithm for data compression. IEEE Trans. Inform. Theor. 23, 3 (May), 337--343.
 
75
Ziv, J. and Lempel, A. 1978. Compression of individual sequences via variable rate coding. IEEE Trans. Inform. Theor. 24, 5 (Sep.), 530--536.


Collaborative Colleagues:
Kenneth C. Barr: colleagues
Krste Asanović: colleagues