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Detecting Faulty Nodes with Data Errors for Wireless Sensor Networks

机译:为无线传感器网络检测具有数据错误的故障节点

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摘要

Wireless Sensor Networks (WSN) promise researchers a powerful instrument for observing sizable phenomena with fine granularity over long periods. Since the accuracy of data is important to the whole system's performance, detecting nodes with faulty readings is an essential issue in network management. As a complementary solution to detecting nodes with functional faults, this article, proposes FIND, a novel method to detect nodes with data faults that neither assumes a particular sensing model nor requires costly event injections. After the nodes in a network detect a natural event, FIND ranks the nodes based on their sensing readings as well as their physical distances from the event. FIND works for systems where the measured signal attenuates with distance. A node is considered faulty if there is a significant mismatch between the sensor data rank and the distance rank. Theoretically, we show that average ranking difference is a provable indicator of possible data faults. FIND is extensively evaluated in simulations and two test bed experiments with up to 25 MicaZ nodes. Evaluation shows that FIND has a less than 5% miss detection rate and false alarm rate in most noisy environments.
机译:无线传感器网络(WSN)为研究人员提供了一种强大的工具,可以长期观察细粒度的可观现象。由于数据的准确性对整个系统的性能很重要,因此检测错误读数的节点是网络管理中的重要问题。作为检测具有功能故障的节点的补充解决方案,本文提出了FIND,这是一种检测具有数据故障的节点的新颖方法,该方法既无需采用特定的传感模型,也不需要进行昂贵的事件注入。网络中的节点检测到自然事件后,FIND会根据节点的感知读数以及它们与事件之间的物理距离对节点进行排名。 FIND适用于被测信号随距离衰减的系统。如果传感器数据等级和距离等级之间存在重大不匹配,则认为节点有故障。从理论上讲,我们表明平均排名差异是可能的数据故障的可证明指标。在多达25个MicaZ节点的仿真和两个试验台实验中,对FIND进行了广泛的评估。评估表明,在大多数嘈杂的环境中,FIND的漏检率和误报率均低于5%。

著录项

  • 来源
    《ACM transactions on sensor networks》 |2014年第3期|40.1-40.27|共27页
  • 作者单位

    University of Minnesota, Twin Cities,Arista Networks, 5453 Great America Parkway, Santa Clara, CA 95054;

    Zhejiang University, Zheda Road 38, Hangzhou, China 310027;

    University of Nebraska-Lincoln, Department of Computer Science & Engineering, Lincoln, NE 68588-0115;

    Zhejiang University, Zheda Road 38, Hangzhou, China 310027;

    University of Tennessee, Knoxville, Department of Electrical Engineering & Computer Science, 1520 Middle Drive, Knoxville, TN 37996-2250;

    University of Minnesota, Twin Cities, 4-205 EE/CSci Building, 200 Union Street SE, Minneapolis, MN 55455;

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  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Wireless sensor networks; data fault detection;

    机译:无线传感器网络;数据故障检测;

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