Shan Anxing, Xu Xianghua, Cheng Zongmao
School of Computer Science, Hangzhou Dianzi University, Hangzhou 310018, China.
School of Science, Hangzhou Dianzi University, Hangzhou 310018, China.
Sensors (Basel). 2016 Aug 27;16(9):1372. 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.
感知覆盖是无线传感器网络（WSN）中的一个基本问题，已经引起了广泛关注。关于这个主题的传统研究集中在0/1覆盖模型上，而这只是对实际感知模型的粗略近似。在本文中，我们研究目标覆盖问题，其目标是基于概率感知模型在随机部署的无线传感器网络中找到最少数量的传感器节点。我们分析了多个传感器对目标的联合检测概率。基于对检测概率的理论分析，我们提出了最小ϵ-检测覆盖问题。我们证明了最小ϵ-检测覆盖问题是NP难的，并提出了一种具有可证明近似比率的近似算法，称为概率传感器覆盖算法（PSCA）。为了评估我们的设计，我们从理论上分析了PSCA的性能，并进行了广泛的仿真以证明我们提出的算法的有效性。
