An Improved Distributed Fault Diagnosis Algorithm in Wireless Sensor Networks

DOI

10.2991/icwcsn-16.2017.132How to use a DOI?

Keywords

wireless sensor networks (wsns); vector space model; cross-sliding window; node fault diagnosis

Abstract

In wireless sensor networks (WSNs), nodes fault diagnosis is the important measure for the continuous monitoring service. Efficient and accurate methods for diagnose nodes fault is a hot research topic in the field of WSNs in the recent years. This paper propose an improved distributed fault diagnosis method namely Cross-Space Distributed Fault Diagnosis (CS-DFD) which follows the DFD algorithm, building high-dimensional vector space model through the collected information from each node, establishing the cross type of sliding window through its historical data and the data from neighbor nodes, setting the cross direction customizable weights of fault. Ultimately, achieving the goal of fault diagnosis by detecting abnormal vector and threshold. The experimental results show that it has reduced the amount of calculation; simplified harsh conditions of fault judgments; reduced the consumption of electricity, etc. which in DFD algorithm. Comparing with the traditional DFD algorithm, the fault diagnosis accuracy improved by 5.14%, the fault of false alarm ratio (FAR) decreased by 2.01% and the time of diagnosis has shortened obviously.

Copyright

© 2017, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Lin Chang
AU  - Zhi-Qing Huang
AU  - Yan-Xin Zhang
PY  - 2016/12
DA  - 2016/12
TI  - An Improved Distributed Fault Diagnosis Algorithm in Wireless Sensor Networks
BT  - Proceedings of the 3rd International Conference on Wireless Communication and Sensor Networks (WCSN 2016)
PB  - Atlantis Press
SP  - 646
EP  - 651
SN  - 2352-538X
UR  - https://doi.org/10.2991/icwcsn-16.2017.132
DO  - 10.2991/icwcsn-16.2017.132
ID  - Chang2016/12
ER  -