Coverability of Wireless Sensor Networks

IF 5.2 1区 计算机科学 Q1 COMPUTER SCIENCE, INFORMATION SYSTEMS
Yin Wang , Zhiyu Huang
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引用次数: 4

Abstract

The coverability of Wireless Sensor Networks (WSNs) is essentially a Quality of Service (QoS) problem that measures how well the monitored area is covered by one or more sensor nodes. The coverability of WSNs was examined by combining existing computational geometry techniques such as the Voronoi diagram and Delaunay triangulation with graph theoretical algorithmic techniques. Three new evaluation algorithms, known as CRM (Comprehensive Risk Minimization), TWS (Threshold Weight Shortest path), and CSM (Comprehensive Support Maximization), were introduced to better measure the coverability. The experimental results show that the CRM and CSM algorithms perform better than the MAM (MAximize Minimum weight) and MIM (MInimize Maximum weight) algorithms, respectively. In addition, the TWS algorithm can provide a lower bound detection possibility that accurately reflects the coverability of the wireless sensor nodes. Both theoretical and experimental analyses show that the proposed CRM, TWS, and CSM algorithms have O(n2) complexity.

无线传感器网络的可覆盖性
无线传感器网络(wsn)的可覆盖性本质上是一个服务质量(QoS)问题,它衡量一个或多个传感器节点对被监视区域的覆盖程度。通过将现有的计算几何技术(如Voronoi图和Delaunay三角剖分)与图理论算法技术相结合,研究了wsn的可覆盖性。引入了三种新的评估算法,即CRM(综合风险最小化)、TWS(阈值权重最短路径)和CSM(综合支持最大化),以更好地衡量可覆盖性。实验结果表明,CRM和CSM算法分别优于MAM (Maximum Minimum weight)和MIM (Minimum Maximum weight)算法。此外,TWS算法可以提供一个下界检测可能性,准确反映无线传感器节点的可覆盖性。理论和实验分析表明,所提出的CRM、TWS和CSM算法的复杂度为0 (n2)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
12.10
自引率
0.00%
发文量
2340
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