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A Distributed Bayesian Algorithm for data fault detection in wireless sensor networks

机译:无线传感器网络中数据故障检测的分布式贝叶斯算法

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This paper proposes a new Distributed Bayesian Algorithm (DBA) for data fault detection in order to address problems of data fault in wireless sensor networks. Although many methods for data fault detection have been proposed, the diagnosis accuracy is still very low especially in the situation of the densely deployed WSN with a large number of faulty nodes. In DBA, the Bayesian network is introduced to calculate the fault probability of sensor nodes, and the fault probability will be adjusted by exploiting the border nodes to improve the accuracy of fault probability and avoid the negative impact of the large number of faulty nodes. A comprehensive simulation has been made to compare the performance of DBA and Distributed Fault Detection (DFD). The simulation results show DBA can improve the fault detection accuracy significantly even in the situation with a large number of faulty nodes.
机译:为了解决无线传感器网络中的数据故障问题,本文提出了一种新的分布式贝叶斯算法(DBA)用于数据故障检测。尽管已经提出了许多用于数据故障检测的方法,但是诊断准确性仍然非常低,特别是在具有大量故障节点的密集部署的WSN的情况下。在DBA中,引入贝叶斯网络来计算传感器节点的故障概率,并通过利用边界节点来调整故障概率,以提高故障概率的准确性,避免大量故障节点的负面影响。已经进行了全面的仿真,以比较DBA和分布式故障检测(DFD)的性能。仿真结果表明,即使在有大量故障节点的情况下,DBA仍可以显着提高故障检测的准确性。

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