A Resource–efficient Time Estimation for Wireless Sensor Networks

KENNETH C. BARR and KRSTE ASANOVIC (MIT Comp. Sci. and A.I. Lab)

Complete Citation

Barr, K. C. and Asanović, K. 2006. Energy-aware lossless data compression. ACM Trans. Comput. Syst. 24, 3 (Aug. 2006), 250-291. DOI= http://doi.acm.org/10.1145/1151690.1151692

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.

Annotations

This paper investigates the possible energy savings achieved when compression is used on network traffic before transmitting it over a wireless link. First the authors note that their measurements that 500 to 1000 add operations can be performed and consume the same amount of energy as transmitting a single bit of data over a wireless link. Thus, the authors investigate using various compression/decompression algorithms on the data, then transmitting it and recording the energy usage at both the sender and receiver.

I like this paper as it gives a good overview of different compression techniques and demonstrates their effectiveness and energy usage. Basically, what they found in their study was that expensive compression algorithms like bzip2 will likely cause the system to consume more energy on both the transmit and receive side then if no compression had been used in the transmission. They also find that simpler methods such as compress.

-- DavidSalyers - 19 Sep 2007