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Masoum, A. and Meratnia, N. and Havinga, P.J.M. (2012) A Decentralized Quality Aware Adaptive Sampling Strategy in Wireless Sensor Networks. In: 9th IEEE International Conference on Ubiquitous Intelligence and Computing, UIC 2012, 4-7 Sep 2012, Fukuoka, Japan. pp. 298-305. IEEE Computer Society. ISBN 978-1-4673-3084-8
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Official URL: http://dx.doi.org/10.1109/UIC-ATC.2012.156
Since WSNs suffer from sever resource constraints, in terms of energy, memory and processing, temporal, spatial and spatio-temporal correlation among sensor data can be exploited by adaptive sampling approaches to find out an optimal sampling strategy, which reduces the number of sampling nodes and/or sampling rates while maintaining high data quality. In this paper, a quality aware decentralized adaptive sampling strategy is proposed which benefit from the data correlation for predicting future samples. In this algorithm, sensor nodes adjust their sampling rates, based on environmental conditions and user defined data range. Simulation results show that proposed approach provides 90 percentage event detection accuracy level while consumes lesser energy rather than existing adaptive sampling approach.
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