北京邮电大学学报

  • EI核心期刊

北京邮电大学学报 ›› 2014, Vol. 37 ›› Issue (s1): 23-29.doi: 10.13190/j.jbupt.2014.s1.005

• 论文 • 上一篇    下一篇

支持向量机回归预测在网络故障检测中的应用

孟洛明1, 朱杰辉1, 杨杨1, 孟玲莉2, 张平平2, 高志鹏1   

  1. 1. 北京邮电大学 网络与交换技术国家重点实验室, 北京 100876;
    2. 国网天津市电力公司, 天津 300010
  • 收稿日期:2013-10-12 出版日期:2014-06-28 发布日期:2014-06-28
  • 作者简介:孟洛明(1955- ),男,教授,博士生导师;朱杰辉(1989- ),男,硕士生,E-mail:int1425@gmail.com.
  • 基金资助:

    国家自然科学基金项目(61272515);国家自然科学基金创新研究群体科学基金项目(61121061);教育部博士点基金项目(20110005110011);国家电网公司科技项目(SGTJXT00XXJS1300048)

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. 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:
     

摘要:

无线传感器网络主要用于收集环境数据,然而传感器可靠性低,容易出现故障并返回异常的监测数据.因此,如何检测传感器故障成为关乎无线传感器网络监测性能的重要问题.提出了基于支持向量机回归预测的故障检测算法,通过充分利用历史数据预测传感器的测量值,并根据测量值与实际值的对比有效地划分信誉等级,最后基于置信数据集计算出的置信条件进行故障的检测.仿真结果证明了算法在节约能量和故障检测率上有着优异的表现.

关键词: 无线传感器网络, 支持向量机回归, 信誉度, 故障检测

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

中图分类号: