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Delaunay Triangulation as a New Coverage Measurement Method in Wireless Sensor Network

机译:Delaunay三角剖分作为一种新的无线传感器网络覆盖率测量方法

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摘要

Sensing and communication coverage are among the most important trade-offs in Wireless Sensor Network (WSN) design. A minimum bound of sensing coverage is vital in scheduling, target tracking and redeployment phases, as well as providing communication coverage. Some methods measure the coverage as a percentage value, but detailed information has been missing. Two scenarios with equal coverage percentage may not have the same Quality of Coverage (QoC). In this paper, we propose a new coverage measurement method using Delaunay Triangulation (DT). This can provide the value for all coverage measurement tools. Moreover, it categorizes sensors as ‘fat’, ‘healthy’ or ‘thin’ to show the dense, optimal and scattered areas. It can also yield the largest empty area of sensors in the field. Simulation results show that the proposed DT method can achieve accurate coverage information, and provides many tools to compare QoC between different scenarios.
机译:传感和通信范围是无线传感器网络(WSN)设计中最重要的折衷方案。在计划,目标跟踪和重新部署阶段以及提供通信覆盖范围时,感知覆盖范围的最小范围至关重要。某些方法将覆盖率以百分比值衡量,但是缺少详细信息。两个具有相同覆盖率的方案可能不会具有相同的覆盖质量(QoC)。在本文中,我们提出了一种使用Delaunay三角剖分(DT)的新覆盖率测量方法。这可以为所有覆盖率测量工具提供价值。此外,它将感应器分为“胖”,“健康”或“瘦”类别,以显示密集,最佳和分散的区域。它还可以产生现场最大的传感器空白区域。仿真结果表明,所提出的DT方法可以实现准确的覆盖信息,并提供了多种工具来比较不同场景之间的QoC。

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