Affiliation:
1. MIT Computer Science and Artificial Intelligence Laboratory, Cambridge, MA
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.
Publisher
Association for Computing Machinery (ACM)
Reference71 articles.
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2. 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.]] 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.]]
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