Energy aware lossless data compression

Abstract

Wireless transmission of a bit can require over 1000 times more energy than a single 32-bit computation. It would therefore seem desirable to perform significant 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 paper reports on the energy of lossless data compressors as measured on a StrongARM SA-110 system. We show 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 hardwareaware programming optimizations are demonstrated. When applied to Unix compress, these optimizations improve energy efficiency by 51%. We also explore the fact that, for many usage models, 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 compressible web data can be reduced 31%. Energy to send harder-to-compress English text can be reduced 57%. Compared with a system using a single optimized application for both compression and decompression, the asymmetric scheme saves 11% or 12% of the total energy depending on the dataset.

Energy-Optimized Image Communication on Resource-Constrained Sensor Platforms

“…Energy-aware data compression has previously been examined by Barr and Asanović in [2], and by Sadler and Martonosi in [3]. Both papers investigate the effectiveness of various lossless data compression algorithms such as "LZO" and "bzip2" on constrained embedded platforms.…”

Threshold cryptography in P2P and MANETs: The case of access control

“…The energy consumption is directly proportional to the processing time and thus it is meaningless to measure energy consumption with all the test cases above. However, it is well known that, in many small devices such as low-end MANET nodes or sensors, sending a single bit is roughly equivalent to performing 1000 32-bit computations in terms of batter power consumption [1]. Therefore, we measured power consumption in terms of communication bandwidth required by each admission protocol.…”

Survey on Enhanced Compressed P-Coding for Energy Efficient Transmission in Mobile Ad Hoc Networks

“…Author Amit Setia and Priyanka Ahlawatet al [4] performed comparison between various text compression methods, [4]- [6] in which ELZW performs better than other compression techniques. ELZW is enhanced LZW where LZW is a part of LZ78 (Lempel-Zip) family.…”