Target Coverage in Wireless Sensor Networks with Probabilistic Sensors

• Published in: Sensors (Basel, Switzerland) Vol. 16; no. 9; p. 1372
• Main Authors: Shan, Anxing, Xu, Xianghua, Cheng, Zongmao
• Format: Journal Article
• Language: English
• Published: Switzerland MDPI AG 27.08.2016; MDPI
• Subjects: Algorithms; Approximation; Computer simulation; Mathematical analysis; Probabilistic methods; probabilistic sensor; Probability theory; Remote sensors; Sensors; target coverage; Wireless networks; Wireless sensor networks; probabilistic sensor; wireless sensor networks; target coverage
• ISSN: 1424-8220; 1424-8220
• DOI: 10.3390/s16091372

Sensing coverage is a fundamental problem in wireless sensor networks (WSNs), which has attracted considerable attention. Conventional research on this topic focuses on the 0/1 coverage model, which is only a coarse approximation to the practical sensing model. In this paper, we study the target coverage problem, where the objective is to find the least number of sensor nodes in randomly-deployed WSNs based on the probabilistic sensing model. We analyze the joint detection probability of target with multiple sensors. Based on the theoretical analysis of the detection probability, we formulate the minimum ϵ-detection coverage problem. We prove that the minimum ϵ-detection coverage problem is NP-hard and present an approximation algorithm called the Probabilistic Sensor Coverage Algorithm (PSCA) with provable approximation ratios. To evaluate our design, we analyze the performance of PSCA theoretically and also perform extensive simulations to demonstrate the effectiveness of our proposed algorithm.