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Energy Aware Lossless Data Compression

By Krste Asanović, Arthur C. Smith and Kenneth C. Barr and Kenneth C. Barr


Wireless transmission of a bit can require over 1000 times more energy than a single 32-bit computation. It may therefore be desirable 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 consequently, a longer battery life for portable computers. This thesis is a study of the energy profiles of lossless data compression algorithms. Several distinct algorithms have been selected and are measured on a StrongARM SA-110 processor. This work demonstrates that with several typical compression tools, there is a net energy increase when compression is applied before transmission. Reasons for this increase are explained and suggestions are made to avoid it. Compression and decompression need not be performed by the same algorithm. By choosing the lowest-energy compressor and decompressor on the test platform, rather than using default levels of compression, overall energy to send data can be reduced 57%. Compared with a system using the same optimized application for both compression and decompression, the asymmetric scheme saves 11% of the total energy

Year: 2000
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