New fault tolerant strategy of wireless sensor network

Afef Ghabri, Leila Horchani, Monia Bellalouna
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引用次数: 5

Abstract

The wireless sensor network is enormously used in a random way in different environments to execute diverse applications and tasks. Because of its sensitivity, various research projects have been conducted with the aim of finding solutions in the presence of failures. New versions of K-means And Traveling Salesman Problem based mobility protocol, based on K-means clustering and the approximate solution for Traveling Salesman Problem by using the simple local search algorithm “2-Opt”, have been proposed in order to obtain real time solutions once the problem is disturbed by the breakdowns of some nodes. In this paper, we aim to use a new strategy by implementing algorithms employed for probabilistic combinatorial optimization problems resolution, such as exact methods. We propose then a new strategy that navigates the mobile sink to go through the cluster centers according to the optimized path by the implementation of an exact resolution of this problem using the “branch and bound” technique. Simulation results have demonstrated that although this exact solution is very expensive, it can be so interesting when the risk of sensor breakdowns becomes considerable and the number of cluster centers will be reduced, and that it outperforms the original solution of K-means And Traveling Salesman Problem based mobility protocol in terms of quality despite the increase in complexity.
无线传感器网络容错新策略
无线传感器网络在不同的环境中以随机方式执行不同的应用和任务。由于其敏感性,已经开展了各种研究项目,目的是在存在故障的情况下寻找解决方案。提出了基于K-means和旅行商问题的移动协议的新版本,该协议基于K-means聚类和旅行商问题的简单局部搜索算法“2-Opt”的近似解,以便在问题受到某些节点故障干扰时获得实时解。在本文中,我们的目标是通过实现用于概率组合优化问题解决的算法,如精确方法,来使用一种新的策略。然后,我们提出了一种新的策略,通过使用“分支定界”技术实现对这一问题的精确解决,使移动sink按照优化路径通过集群中心。仿真结果表明,尽管这种精确的解决方案非常昂贵,但当传感器故障的风险变得相当大并且集群中心的数量将减少时,它可以变得非常有趣,并且尽管复杂性增加,但它在质量方面优于基于K-means和旅行推销员问题的移动协议的原始解决方案。
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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