A Fault Detection Algorithm for Wireless Sensor Networks Based on Support Vector Regression

doi:10.13190/j.jbupt.2014.s1.005

JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM ›› 2014, Vol. 37 ›› Issue (s1): 23-29.doi: 10.13190/j.jbupt.2014.s1.005

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A Fault Detection Algorithm for Wireless Sensor Networks Based on Support Vector Regression

MENG Luo-ming¹, ZHU Jie-hui¹, YANG Yang¹, MENG Ling-li², ZHANG Ping-ping², GAO Zhi-peng¹

1. State Key Laboratory of Networking and Switching Technology, Beijing University of Posts and Telecommunications, Beijing 100876, China;
2. State Grid TianJin Electric Power Company, Tianjin 300010, China

Received:2013-10-12 Online:2014-06-28 Published:2014-06-28
Supported by:

Abstract

Abstract:

The main role of wireless sensor networks is to collect environmental data. As for the sensor nodes are vulnerable and work in unpredictable environments, the sensors are possible out off work and return to unexpected response. Therefore, fault detection is important in wireless sensor networks. The authors propose a fault detection algorithm based on support vector regression, which predicts the measurements of sensor nodes by using historical data. Credit levels of sensor nodes will be determined by a contrast between predictions and actual measured values. Then the dependable data set which is constructed by high credit level measurements will be used to detect sensor faults. Simulations demonstrate that the algorithm works very well in conserving energy and raising failure detection rate.

Key words: wireless sensor network, support vector regression, credibility level, fault detection

CLC Number:

TP212
V241.6

MENG Luo-ming, ZHU Jie-hui, YANG Yang, MENG Ling-li, ZHANG Ping-ping, GAO Zhi-peng. A Fault Detection Algorithm for Wireless Sensor Networks Based on Support Vector Regression[J]. JOURNAL OF BEIJING UNIVERSITY OF POSTS AND TELECOM, 2014, 37(s1): 23-29.

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A Fault Detection Algorithm for Wireless Sensor Networks Based on Support Vector Regression

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