Green Communications and Networking. First International Conference, GreeNets 2011, Colmar, France, October 5-7, 2011, Revised Selected Papers

Research Article

A Flexible Boundary Sensing Model for Group Target Tracking in Wireless Sensor Networks

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  • @INPROCEEDINGS{10.1007/978-3-642-33368-2_3,
        author={Quanlong Li and Zhijia Zhao and Xiaofei Xu and Qingjun Yan},
        title={A Flexible Boundary Sensing Model for Group Target Tracking in Wireless Sensor Networks},
        proceedings={Green Communications and Networking. First International Conference, GreeNets 2011, Colmar, France, October 5-7, 2011, Revised Selected Papers},
        proceedings_a={GREENETS},
        year={2012},
        month={11},
        keywords={Sensor Networks Sensing Model Boundary Sensing Model Group Target Tracking},
        doi={10.1007/978-3-642-33368-2_3}
    }
    
  • Quanlong Li
    Zhijia Zhao
    Xiaofei Xu
    Qingjun Yan
    Year: 2012
    A Flexible Boundary Sensing Model for Group Target Tracking in Wireless Sensor Networks
    GREENETS
    Springer
    DOI: 10.1007/978-3-642-33368-2_3
Quanlong Li1,*, Zhijia Zhao1, Xiaofei Xu1, Qingjun Yan1
  • 1: Harbin Institute of Technology
*Contact email: liquanlong@hit.edu.cn

Abstract

Group target usually covers a large area and is more difficult to track in wireless sensor networks. In traditional methods, much more sensors are activated and involved in tracking, which causes a heavy network burden and huge energy cost. This paper presents a Boundary Sensing Model (BSM) used to discover group target’s contour, which conserves energy by letting only a small number of sensors – BOUNDARY sensors participate in tracking. Unlike previous works, the proposed BSM is flexible by adjusting the boundary thickness thresholds. We analytically evaluate the probability of becoming a BOUNDARY sensor and the average quantity of BOUNDARY sensors, which proved to be affected by communication radius, density, and boundary thickness thresholds. Extensive simulation results confirm that our theoretical results are reasonable, and show that our proposed BSM based group target tracking method uses less number of sensors for group tracking without precision loss.