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Heterogeneous fault diagnosis for wireless sensor networks

机译:无线传感器网络的异构故障诊断

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Fault diagnosis has been considered as a very challenging problem in wireless sensor network (WSN) research. Faulty nodes having different behavior such as hard, soft, intermittent, and transient fault are called as heterogeneous faults in wireless sensor networks. This paper presents a heterogeneous fault diagnosis protocol for wireless sensor networks. The proposed protocol consists of three phases, such as clustering phase, fault detection phase, and fault classification phase to diagnose the heterogeneous faulty nodes in the wireless sensor networks. The protocol strategy is based on time out mechanism to detect the hard faulty nodes, and analysis of variance method (ANOVA test) to detect the soft, intermittent, and transient faulty nodes in the network. The feed forward probabilistic neural network (PNN) technique is used to classify the different types of faulty nodes in the network. The performance of the proposed heterogeneous fault diagnosis protocol is evaluated using network simulator NS-2.35. The evaluation of the proposed model is also carried out by the testbed experiment in an indoor laboratory environment and outdoor environment. (c) 2017 Elsevier B.V. All rights reserved.
机译:在无线传感器网络(WSN)研究中,故障诊断已被认为是一个非常具有挑战性的问题。在无线传感器网络中,具有不同行为(例如硬,软,间歇和暂态故障)的故障节点称为异构故障。本文提出了一种用于无线传感器网络的异构故障诊断协议。所提出的协议包括三个阶段,例如聚类阶段,故障检测阶段和故障分类阶段,以诊断无线传感器网络中的异构故障节点。协议策略基于超时机制来检测硬故障节点,并采用方差分析法(ANOVA测试)来检测网络中的软故障,间歇故障和瞬态故障节点。前馈概率神经网络(PNN)技术用于对网络中故障节点的不同类型进行分类。使用网络模拟器NS-2.35对提出的异构故障诊断协议的性能进行了评估。还通过在室内实验室环境和室外环境中进行的试验台实验对提出的模型进行了评估。 (c)2017 Elsevier B.V.保留所有权利。

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