Analyzing object detection quality under probabilistic coverage in sensor networks

  • Authors:
  • Shansi Ren;Qun Li;Haining Wang;Xin Chen;Xiaodong Zhang

  • Affiliations:
  • College of William and Mary, Williamsburg, VA;College of William and Mary, Williamsburg, VA;College of William and Mary, Williamsburg, VA;College of William and Mary, Williamsburg, VA;College of William and Mary, Williamsburg, VA

  • Venue:
  • IWQoS'05 Proceedings of the 13th international conference on Quality of Service
  • Year:
  • 2005

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Abstract

Object detection quality and network lifetime are two conflicting aspects of a sensor network, but both are critical to many sensor applications such as military surveillance. Probabilistic coverage is an appropriate approach to balancing the conflicting design requirements of monitoring applications. Under probabilistic coverage, we present an analytical model to analyze object detection quality with respect to different network conditions and sensor scheduling schemes. Our analytical model facilitates performance evaluation of a sensing schedule, network deployment, and sensing scheduling protocol design. Applying the model to real sensor networks, we design a set of sensing scheduling protocols to achieve targeted object detection quality while minimizing power consumption. The correctness of our model and the effectiveness of the proposed protocols are validated through extensive simulation experiments.