一种基于Elfes模型的无线传感器网络覆盖孔识别方案

Cheng Chen, Bin Wang, Bowen Huang
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引用次数: 0

摘要

覆盖是评价无线传感器网络服务质量的重要指标。由于节点的随机部署,节点能量耗尽或节点故障等事件会导致传感领域出现覆盖漏洞,影响无线传感器网络提供的服务质量。本文提出了在Elfes模型下,基于给定阈值检测概率的有效覆盖空洞识别算法。该算法的思想是首先在故障节点周围的最大感知范围内,通过消除故障节点内部由相邻节点形成的冗余区域,构建候选覆盖孔。给定候选覆盖漏洞和指定阈值检测概率,在Elfes模型下通过随机抽样识别覆盖漏洞。与Elfes模型下的现有工作相比,仿真结果表明,该算法在识别覆盖洞时显著减少了随机采样点的数量。此外,当故障节点周围没有覆盖孔时,我们的方案不需要随机抽样。从而提高了覆盖孔识别的效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Coverage Hole Identification Scheme for Wireless Sensor Networks Based on Elfes Model
Coverage is an important metric for evaluating quality of service provided by wireless sensor networks (WSNs). Due to random deployment of nodes, events such as node energy exhaustion or node failure will lead to emergence of coverage holes in the sensing field and affect quality of service provided by wireless sensor networks. This paper proposes an efficient coverage hole identification algorithm under the Elfes model by a given threshold detection probability. The idea of the proposed algorithm is to first construct candidate coverage holes within the maximum sensing range around a faulty node by eliminating redundant area within it formed by its neighbors. Given the candidate coverage holes and specified threshold detection probability, coverage holes are identified under the Elfes model by random sampling. Compared with the existing work under the Elfes model, simulation results show that the presented algorithm significantly reduce the number of random points to be sampled when identifying coverage holes. In addition, when there are no coverage holes around a faulty node, no random sampling is necessary for our scheme. Hence efficiency of coverage hole identification is improved.
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