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

Author

Zhao, Xiaodong ; Gao, Zhipeng ; Huang, Rimao ; Wang, Zhuoqi ; Wang, Teng

Author_Institution

State Key Lab. of Networking & Switching Technol., Beijing Univ. of Posts & Telecommun., Beijing, China

fYear

2011

fDate

16-18 Dec. 2011

Firstpage

354

Lastpage

355

Abstract

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.

Keywords

fault diagnosis; wireless sensor networks; WSN; cluster analysis; distributed Bayesian algorithms; distributed fault detection algorithm; fault nodes; k-means cluster fault detection algorithm; wireless sensor networks; Accuracy; Algorithm design and analysis; Bayesian methods; Clustering algorithms; Educational institutions; Fault detection; Wireless sensor networks; Cluster Analysis; fault detection; k-means clustering; wireless sensor networks;

fLanguage

English

Publisher

ieee

Conference_Titel

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

Conference_Location

Beijing

Print_ISBN

978-1-4577-2178-6

Type

conf

DOI

10.1109/MSN.2011.59

Filename

6117441