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一种确保具有不确定属性的无线传感器网络实现多级覆盖的有效传感器部署方案。

An Effective Sensor Deployment Scheme that Ensures Multilevel Coverage of Wireless Sensor Networks with Uncertain Properties.

作者信息

Chen Yu-Ning, Lin Wu-Hsiung, Chen Chiuyuan

机构信息

Department of Applied Mathematics, National Chiao Tung University, Hsinchu 300, Taiwan.

出版信息

Sensors (Basel). 2020 Mar 25;20(7):1831. doi: 10.3390/s20071831.

DOI:10.3390/s20071831
PMID:32218366
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7181270/
Abstract

The coverage problem is a fundamental problem for almost all applications in wireless sensor networks (WSNs). Many applications even impose the requirement of multilevel () coverage of the region of interest (ROI). In this paper, we consider WSNs with uncertain properties. More precisely, we consider WSNs under the probabilistic sensing model, in which the detection probability of a sensor node decays as the distance between the target and the sensor node increases. The difficulty we encountered is that there is unified definition of -coverage under the probabilistic sensing model. We overcome this difficulty by proposing a "reasonable" definition of -coverage under such a model. We propose a sensor deployment scheme that uses less number of deployed sensor nodes while ensuring good coverage qualities so that (i) the resultant WSN is connected and (ii) the detection probability satisfies a predefined threshold p th , where 0 < p th < 1 . Our scheme uses a novel "zone 1 and zone 1-2" strategy, where zone 1 and zone 2 are a sensor node's sensing regions that have the highest and the second highest detection probability, respectively, and zone 1-2 is the union of zones 1 and 2. The experimental results demonstrate the effectiveness of our scheme.

摘要

覆盖问题是无线传感器网络(WSN)中几乎所有应用的一个基本问题。许多应用甚至对感兴趣区域(ROI)提出了多级()覆盖的要求。在本文中,我们考虑具有不确定属性的WSN。更确切地说,我们考虑概率感知模型下的WSN,其中传感器节点的检测概率随着目标与传感器节点之间距离的增加而衰减。我们遇到的困难是,在概率感知模型下没有统一的-覆盖定义。我们通过在这种模型下提出一个“合理的”-覆盖定义来克服这个困难。我们提出了一种传感器部署方案,该方案在确保良好覆盖质量的同时使用较少数量的已部署传感器节点,以便(i)所得的WSN是连通的,并且(ii)检测概率满足预定义阈值(p_{th}),其中(0 < p_{th} < 1)。我们的方案使用一种新颖的“区域1和区域1-2”策略,其中区域1和区域2分别是传感器节点具有最高和次高检测概率的感知区域,区域1-2是区域1和区域2的并集。实验结果证明了我们方案的有效性。

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