Energy-Efficient Barrier Coverage With Probabilistic Sensors in Wireless Sensor Networks

Abstract

Barrier coverage is an important research issue in wireless sensor networks (WSNs). Barrier gaps may exist due to deployment randomness or battery depletion. It is critical to address the problem with an energy-efficient method due to the high cost of mobile sensors. Besides, it is a challenge to introduce the realistic probabilistic sensing model of sensors while mending barrier gaps. In this paper, we study how to efficiently use mobile sensors with a probabilistic sensing model to improve barrier coverage. Firstly, we define safe cell and design algorithms to find safe cells and barrier gaps. Secondly, we study how to improve the barrier coverage with minimum number of mobile sensors. Thirdly, we divide minimum movement of mobile sensors problem into the simple case and general case, and the general case is resorted to Kuhn-Munkres (KM) algorithm. Simulation results are conducted to demonstrate the effectiveness and advantage of our proposed algorithms.