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A distributed fault recovery method in clustering-based Wireless Sensor networks

机译:基于集群的无线传感器网络中的分布式故障恢复方法

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Wireless Sensor Network (WSN) is fault-prone given the resource-constrained characteristic of sensors and harsh deployment environment. Failure of sensors may cause negative consequences on the considered applications. Therefore, WSN should be able to tolerate the failures of sensors and self-recover from fault to guarantee the service. However current studies mostly focus on fault diagnosis, and little research has been done on fault recovery. In this paper, we propose a Distributed Fault Recovery Approach (DFRA) for the networks' self-restore in case of failures with minimized calculate and communication overhead. Fuzzy theory is introduced to model the fault-recovery problem. To find an optimal replacement scheme, genetic algorithm and simplex method are adopted and converged. A fusion algorithm named genetic simplex method algorithm (GSMA) is proposed. At last, the simulation shows that GSMA has better performance and achieves longer network lifetime through the execution of the fault recovery approach.
机译:考虑到传感器的资源受限特性和恶劣的部署环境,无线传感器网络(WSN)容易出错。传感器故障可能会对所考虑的应用造成负面影响。因此,WSN应该能够容忍传感器的故障并能够从故障中自动恢复以保证服务。然而,当前的研究主要集中在故障诊断上,而关于故障恢复的研究很少。在本文中,我们提出了一种分布式故障恢复方法(DFRA),用于在发生故障时以最小的计算和通信开销实现网络的自我恢复。引入模糊理论对故障恢复问题进行建模。为了找到最佳的替换方案,采用遗传算法和单纯形法进行了收敛。提出了一种融合算法,称为遗传单纯形法算法(GSMA)。最后,仿真表明,通过执行故障恢复方法,GSMA具有更好的性能并实现了更长的网络寿命。

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