A Multi-Objective Evolutionary Approach To Data Co Essay

4622 WordsFeb 6, 201219 Pages
2009 Ninth International Conference on Intelligent Systems Design and Applications A Multi-objective Evolutionary Approach to Data Compression in Wireless Sensor Networks Francesco Marcelloni Dipartimento di Ingegneria dell’Informazione University of Pisa Via Diotisalvi 2, 56122 Pisa - ITALY f.marcelloni@iet.unipi.it Massimo Vecchio ASAP Research Group INRIA Saclay, Ile de France sud 4, Rue J. Monod, 91893 Orsay Cedex - FRANCE massimo.vecchio@inria.fr Abstract—Energy is a primary constraint in the design and deployment of wireless sensor networks (WSNs) since sensor nodes are typically powered by batteries with a limited capacity. Since radio communication is, in general, the most energy hungry operation in a sensor node, most of the techniques proposed to extend the lifetime of a WSN have focused on limiting transmission/reception of data, for instance, through data compression. Since sensor nodes are equipped with limited computational and storage resources, enabling compression requires specifically designed algorithms. In this paper, we propose a lossy compressor based on a differential pulse code modulation scheme with quantization of the differences between consecutive samples. The quantization parameters, which allow achieving the desired trade-off between compression performance and information loss, are determined by a multi-objective evolutionary algorithm. Experiments carried out on three datasets collected by real WSN deployments show that our approach can achieve significant compression ratios despite negligible reconstruction errors. Keywords-Wireless sensor networks; data compression; multi-objective genetic algorithms; energy efficiency; signal processing; I. I NTRODUCTION A wireless sensor network (WSN) consists of a set of autonomous systems, called sensor nodes, communicating among themselves and deployed in large scale (from tens to
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