On optimisation of cluster-based sensor network tracking system

  • Authors:

  • Yongcai Wang;Qianchuan Zhao;Dazhong Zheng;Xiaohong Guan

  • Affiliations:

  • Institute for Interdisciplinary Information Sciences IIIS, Tsinghua University, Beijing, 100084, China;Center For Intelligent and Networked System CFINS, Department of Automation, Tsinghua University, Beijing, 100084, China;Center For Intelligent and Networked System CFINS, Department of Automation, Tsinghua University, Beijing, 100084, China;Center For Intelligent and Networked System CFINS, Department of Automation, Tsinghua University, Beijing, 100084, China

  • Venue:
  • International Journal of Ad Hoc and Ubiquitous Computing
  • Year:
  • 2013

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Abstract

Tracking mobile targets using low-cost wireless sensor network WSN requires not only good tracking accuracy but also network longevity. Cluster-based tracking protocols leverage the fact that only sensors in the vicinity of the target can contribute to target detection, while other sensors should sleep to save energy, which provides good tradeoff between energy efficiency and tracking accuracy. However, for the complexity of cluster-based tracking protocols, it is challenging to quantify the tradeoff between energy efficiency and tracking accuracy. In this paper, a convolution-based method is presented to quantify the relationship between the cluster parameters and the energy-quality metrics of the tracking system, which provides Pareto optimal parameters to jointly optimise the energy efficiency and the tracking accuracy of cluster-based WSN tracking system. The presented results are verified in popular cluster-based tracking protocols via extensive simulations, which shows the effectiveness of the optimisation framework.