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A Fault Detection Algorithm Based on Cluster Analysis in Wireless Sensor Networks

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5 Author(s)
Xiaodong Zhao ; State Key Lab. of Networking & Switching Technol., Beijing Univ. of Posts & Telecommun., Beijing, China ; Zhipeng Gao ; Rimao Huang ; Zhuoqi Wang
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In this paper, we present a distributed fault detection algorithm based on k-means clustering for WSN. The nodes within a cluster are divided into three sub-clustering according to their measurements' similarity. We conclude the sensor nodes' working state from the N recent states of sub-clustering, so as to detect, locate, and get rid of the fault nodes. Simulation results show that the k-means cluster fault detection algorithm has a better performance than the distributed Bayesian algorithms. Moreover, the computational complexity of the proposed algorithm is low.

Published in:

Mobile Ad-hoc and Sensor Networks (MSN), 2011 Seventh International Conference on

Date of Conference:

16-18 Dec. 2011