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Sensors 2007, 7(3), 251-266;

Prediction-based Dynamic Energy Management in Wireless Sensor Networks

State Key Laboratory of Precision Measurement Technology and Instruments, Department of Precision Instruments, Tsinghua University, Beijing 100084, P. R. China
Author to whom correspondence should be addressed.
Received: 28 January 2007 / Accepted: 1 March 2007 / Published: 5 March 2007
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Energy consumption is a critical constraint in wireless sensor networks. Focusing on the energy efficiency problem of wireless sensor networks, this paper proposes a method of prediction-based dynamic energy management. A particle filter was introduced to predict a target state, which was adopted to awaken wireless sensor nodes so that their sleep time was prolonged. With the distributed computing capability of nodes, an optimization approach of distributed genetic algorithm and simulated annealing was proposed to minimize the energy consumption of measurement. Considering the application of target tracking, we implemented target position prediction, node sleep scheduling and optimal sensing node selection. Moreover, a routing scheme of forwarding nodes was presented to achieve extra energy conservation. Experimental results of target tracking verified that energy-efficiency is enhanced by prediction-based dynamic energy management. View Full-Text
Keywords: Wireless sensor network; dynamic energy management; energy efficiency; particle filter. Wireless sensor network; dynamic energy management; energy efficiency; particle filter.
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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MDPI and ACS Style

Wang, X.; Ma, J.-J.; Wang, S.; Bi, D.-W. Prediction-based Dynamic Energy Management in Wireless Sensor Networks. Sensors 2007, 7, 251-266.

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