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Distributed Peer-to-Peer Target Tracking in Wireless Sensor Networks
Article

Cluster-based Dynamic Energy Management for Collaborative Target Tracking in Wireless Sensor Networks

State Key Laboratory of Precision Measurement Technology and Instrument, Tsinghua University, Beijing 100084, P. R. China
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Sensors 2007, 7(7), 1193-1215; https://doi.org/10.3390/s7071193
Received: 26 June 2007 / Accepted: 12 July 2007 / Published: 13 July 2007
A primary criterion of wireless sensor network is energy efficiency. Focused onthe energy problem of target tracking in wireless sensor networks, this paper proposes acluster-based dynamic energy management mechanism. Target tracking problem isformulated by the multi-sensor detection model as well as energy consumption model. Adistributed adaptive clustering approach is investigated to form a reasonable routingframework which has uniform cluster head distribution. Dijkstra’s algorithm is utilized toobtain optimal intra-cluster routing. Target position is predicted by particle filter. Thepredicted target position is adopted to estimate the idle interval of sensor nodes. Hence,dynamic awakening approach is exploited to prolong sleep time of sensor nodes so that theoperation energy consumption of wireless sensor network can be reduced. The sensornodes around the target wake up on time and act as sensing candidates. With the candidatesensor nodes and predicted target position, the optimal sensor node selection is considered.Binary particle swarm optimization is proposed to minimize the total energy consumptionduring collaborative sensing and data reporting. Experimental results verify that theproposed clustering approach establishes a low-energy communication structure while theenergy efficiency of wireless sensor networks is enhanced by cluster-based dynamic energymanagement. View Full-Text
Keywords: Wireless sensor network; clustering; dynamic energy management; binary particle swarm optimization. Wireless sensor network; clustering; dynamic energy management; binary particle swarm optimization.
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MDPI and ACS Style

Wang, X.; Ma, J.-J.; Wang, S.; Bi, D.-W. Cluster-based Dynamic Energy Management for Collaborative Target Tracking in Wireless Sensor Networks. Sensors 2007, 7, 1193-1215. https://doi.org/10.3390/s7071193

AMA Style

Wang X, Ma J-J, Wang S, Bi D-W. Cluster-based Dynamic Energy Management for Collaborative Target Tracking in Wireless Sensor Networks. Sensors. 2007; 7(7):1193-1215. https://doi.org/10.3390/s7071193

Chicago/Turabian Style

Wang, Xue, Jun-Jie Ma, Sheng Wang, and Dao-Wei Bi. 2007. "Cluster-based Dynamic Energy Management for Collaborative Target Tracking in Wireless Sensor Networks" Sensors 7, no. 7: 1193-1215. https://doi.org/10.3390/s7071193

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