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Distributed fault detection based on HMM for Wireless Sensor Networks

机译:基于HMM的无线传感器网络分布式故障检测

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In their practical applications, Wireless Sensor Networks (WSNs) can experience faults during running. Furthermore, faulty data collected in the base station might lead to a wrong judgement. Since the whole system's performance require the accuracy of data, node fault detection is necessary. Motivated by the requirement of fault detection performance, we propose a distributed fault detection algorithm for wireless senor networks based on Hidden Markov Model (HMM). Firstly, a density of probability method is presented to obtain the possibility of translation of state for each node in the network. Then, a HMM is introduced to characterize the tendency of each node to be faulty. Finally, a distributed fault detection algorithm is proposed based on the HMM. Simulation results show that the proposed HMM-based fault detection achieves high detection accuracy.
机译:在其实际应用中,无线传感器网络(WSN)可能会在运行过程中遇到故障。此外,基站中收集的错误数据可能会导致错误的判断。由于整个系统的性能需要数据的准确性,因此必须进行节点故障检测。基于故障检测性能的需求,提出了一种基于隐马尔可夫模型(HMM)的分布式传感器网络故障检测算法。首先,提出了一种概率密度方法,以获得网络中每个节点状态转换的可能性。然后,引入HMM来表征每个节点的故障趋势。最后,提出了一种基于HMM的分布式故障检测算法。仿真结果表明,基于HMM的故障检测方法具有较高的检测精度。

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