Vol. 9, No. 4, April 29, 2015
10.3837/tiis.2015.04.005,
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Abstract
Energy efficiency is critical for Wireless Sensor Networks (WSNs) since sensor nodes usually have very limited energy supply from battery. Sleep scheduling and nodes cooperation are two of the most efficient methods to achieve energy conservation in WSNs. In this paper, we propose an adaptive energy optimization approach for target tracking applications, called Energy-Efficient Node Coordination (EENC), which is based on the grid structure. EENC provides an unambiguous calculation and analysis for optimal the nodes cooperation theoretically. In EENC, the sleep schedule of sensor nodes is locally synchronized and globally unsynchronized. Locally in each grid, the sleep schedule of all nodes is synchronized by the grid head, while globally the sleep schedule of each grid is independent and is determined by the proposed scheme. For dynamic sleep scheduling in tracking state we propose a multi-level coordination algorithm to find an optimal nodes cooperation of the network to maximize the energy conservation while preserving the tracking performance. Experimental results show that EENC can achieve energy saving of at least 38.2% compared to state-of-the-art approaches.
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Cite this article
[IEEE Style]
J. Feng, B. Lian, H. Zhao, "Adaptive Energy Optimization for Object Tracking in Wireless Sensor Network," KSII Transactions on Internet and Information Systems, vol. 9, no. 4, pp. 1359-1375, 2015. DOI: 10.3837/tiis.2015.04.005.
[ACM Style]
Juan Feng, Baowang Lian, and Hongwei Zhao. 2015. Adaptive Energy Optimization for Object Tracking in Wireless Sensor Network. KSII Transactions on Internet and Information Systems, 9, 4, (2015), 1359-1375. DOI: 10.3837/tiis.2015.04.005.
[BibTeX Style]
@article{tiis:20769, title="Adaptive Energy Optimization for Object Tracking in Wireless Sensor Network", author="Juan Feng and Baowang Lian and Hongwei Zhao and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2015.04.005}, volume={9}, number={4}, year="2015", month={April}, pages={1359-1375}}