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Fault Localization Using Passive End-to-End Measurements and Sequential Testing for Wireless Sensor Networks

机译:使用无线传感器网络的端到端无源测量和顺序测试进行故障定位

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Faulty components in a network need to be localized and repaired to sustain the health of the network. In this paper, we propose a novel approach that carefully combines active and passive measurements to localize faults in wireless sensor networks. More specifically, we formulate a problem of optimal sequential testing guided by end-to-end data. This problem determines an optimal testing sequence of network components based on end-to-end data in sensor networks to minimize expected testing cost. We prove that this problem is NP-hard, and propose a recursive approach to solve it. This approach leads to a polynomial-time optimal algorithm for line topologies while requiring exponential running time for general topologies. We further develop two polynomial-time heuristic schemes that are applicable to general topologies. Extensive simulation shows that our heuristic schemes only require testing a very small set of network components to localize and repair all faults in the network. Our approach is superior to using active and passive measurements in isolation. It also outperforms the state-of-the-art approaches that localize and repair all faults in a network.
机译:需要对网络中的故障组件进行定位和维修,以维持网络的健康。在本文中,我们提出了一种新颖的方法,该方法将主动和被动测量仔细结合以定位无线传感器网络中的故障。更具体地说,我们提出了一个以端到端数据为指导的最佳顺序测试问题。此问题基于传感器网络中的端到端数据确定网络组件的最佳测试顺序,以最大程度地减少预期的测试成本。我们证明此问题是NP难题,并提出了一种递归方法来解决。这种方法导致针对线形拓扑的多项式时间最优算法,而对于常规拓扑则需要指数运行时间。我们进一步开发了两个适用于一般拓扑的多项式时间启发式方案。广泛的仿真表明,我们的启发式方案只需要测试很少的网络组件即可定位和修复网络中的所有故障。我们的方法优于单独使用主动和被动测量。它也优于对网络中所有故障进行定位和修复的最新方法。

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