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Entropy-based High-Accuracy Distributed Faulty Sensor Detection Algorithm in Wireless Sensor Networks

机译:基于熵的高精度分布式故障传感器检测算法在无线传感器网络中

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Sensor node in wireless sensor networks, due to the unstable conditions they are exposed to, are usually prone to errors which cause the sensor readings to be faulty and usually pose problems on the reliability and security of the whole sensing systems. In this paper, we propose a distributed faulty sensor detection algorithm using entropy. Besides fault detection, our method also corrects the faulty readings. To the best of our knowledge, we are the first one to propose a system entropy concept from thermodynamics and information theory to solve this problem. Our algorithm, compared with previously proposed approaches, accepts any scalar value as input and is faulty probability independent. It is distributed and localized and thus it is scalable. Our method can be applied to any wireless sensor network to help increasing the reliability of the whole system. Simulation results show that our algorithm can detect and recover above 98% of faulty readings when the fault probability is 0.2 which is much more efficient than previous results.
机译:无线传感器网络中的传感器节点,由于它们暴露的不稳定条件,通常容易出错,这导致传感器读数有故障,并且通常对整个传感系统的可靠性和安全性构成问题。在本文中,我们提出了一种使用熵的分布式故障传感器检测算法。除了故障检测外,我们的方法还纠正了错误的读数。据我们所知,我们是第一个提出从热力学和信息理论来解决这个问题的系统熵概念的人。与先前提出的方法相比,我们的算法接受任何标量值作为输入,并且是有缺陷的概率。它是分布式和本地化的,因此它是可扩展的。我们的方法可以应用于任何无线传感器网络,以帮助提高整个系统的可靠性。仿真结果表明,当故障概率为0.2时,我们的算法可以检测和恢复超过98%的有故障读数的读数,这比以前的结果更有效。

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