Communications of the ACS, Vol 3, No 2 (2010)

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Energy Efficient Data Compression technique for Wireless Sensor Networks in Tolerant End-to-End Delay Monitoring Applications

Bouabdellah KECHAR, BIDAI zahia


Energy is an important issue in designing wireless sensor networks (WSN). One natural approach to achieve minimum energy consumption in WSN is the possibility to compress sensed data to be transmitted from source nodes to a common destination (base station or sink). This is usually motivated by the fact that data processing in WSN consumes much less power than data transmission. A data compression technique aims to reduce the amount of transmitted data but with a supplementary data processing. In this paper, we propose a new approach of data compression based on the polynomial approximation to reduce considerably energy consumption at each sensor node, and consequently to extend the WSN life time. Our approach is based on the Stone-Weierstrass theorem from the approximation of functions theory enabling the construction of compressed forms (polynomials with degree m) which will be transmitted from each sensor node towards the sink instead of raw collected data (n measurements of temperature, wind speed, humidity). It exploits the temporal coherency that characterizes a sequence of readings sensed by a node dedicated to supervise a natural phenomenon for which the end-to-end delay of data transmission is tolerated and the nature of the analysis of this data is qualitative. We use computer simulation under Matlab and NS2 environments to demonstrate the effectiveness of this approach in terms of compression quality with a better precision and energy saving by comparing it with other existing similar approaches.

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