Distributed fault detection for wireless sensor network based on cumulative sum control chart

doi:10.11772/j.issn.1001-9081.2016.11.3016

Journal of Computer Applications ›› 2016, Vol. 36 ›› Issue (11): 3016-3020.DOI: 10.11772/j.issn.1001-9081.2016.11.3016

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Distributed fault detection for wireless sensor network based on cumulative sum control chart

LIU Qiuyue¹, CHENG Yong², WANG Jun^1,2, ZHONG Shuiming¹, XU Liya³

1. School of Computer & Software, Nanjing University of Information Science & Technology, Nanjing Jiangsu 210044, China;
2. Department of Information Construction & Management, Nanjing University of Information Science & Technology, Nanjing Jiangsu 210044, China;
3. School of Information Science and Technology, Jiujiang University, Jiujiang Jiangxi 332005, China

Received:2016-05-25 Revised:2016-06-30 Online:2016-11-10 Published:2016-11-12
Supported by:
This work is partially supported by the National Natural Science Foundation of China (61373064,61402236), the Jiangsu Provincial Key Laboratory of Agricultural Meteorology Fund (KYQ1309), the Jiangsu Province "the Peak of the Six Talents" Project (2015-DZXX-015,2013-DZXX-01), the Prospective Joint Research Project of Jiangsu Province (BY2014007-2), the Youth Science Foundation of Jiangxi Province (20151BAB217015), the Public Interest Industry (Meteorological) Special Research Project (GYHY201106037).

基于累积和控制图的分布式传感网络故障诊断

刘秋玥¹, 程勇², 王军^1,2, 钟水明¹, 徐利亚³

1. 南京信息工程大学计算机与软件学院, 南京 210044;
2. 南京信息工程大学信息化建设与管理处, 南京 210044;
3. 九江学院信息科学与技术学院, 江西九江 332005

通讯作者: 刘秋玥
作者简介:刘秋玥(1991-),女,江苏南京人,硕士研究生,主要研究方向:无线传感器网络故障诊断;程勇(1980-),男,重庆人,讲师,博士,CCF会员,主要研究方向:无线传感器网络数据收集、大数据应用;王军(1970-),男,安徽铜陵人,教授,硕士,CCF会员,主要研究方向:无线传感网、大数据应用。
基金资助:
国家自然科学基金资助项目（61402236，61373064）；江苏省农业气象重点实验室开放基金资助项目（KYQ1309）；江苏省“六大人才高峰”项目（2015-DZXX-015，2013-DZXX-019）；江苏省产学研前瞻性联合研究项目（BY2014007-2）；江西省青年科学基金资助项目（20151BAB217015）；公益性行业（气象）科研专项（GYHY201106037）。

Abstract

Abstract: With the stringent resources and distributed nature in wireless sensor networks, fault diagnosis of sensor nodes faces great challenges. In order to solve the problem that the existing approaches of diagnosing sensor networks have high false alarm ratio and considerable computation redundancy on nodes, a new fault detection mechanism based on Cumulative Sum Chart (CUSUM) and neighbor-coordination was proposed. Firstly, the historical data on a single node were analyzed by CUSUM to improve the sensitivity of fault diagnosis and locate the change point. Then, the fault nodes were detected though judging the status of nodes by the data exchange between neighbor nodes. The experimental results show that the detection accuracy is over 97.7% and the false alarm ratio is below 2% when the sensor fault probability in wireless sensor networks is up to 35%. Hence, the proposed algorithm has a high detection accuracy and low false alarm ratio even in the conditions of high fault probabilities and reduces the influence of sensor fault probability clearly.

Key words: Wireless Sensor Network (WSN), fault diagnosis, distributed, cumulative sum control chart, median absolute deviation

摘要： 由于无线气象传感网具有资源受限及分布式等特点，传感器节点的故障诊断面临着很大挑战。针对现有诊断方法误报率高、计算冗余量大的问题，提出了一种基于累积和控制图（CUSUM）与邻居协作融合的故障诊断方法。首先，通过累积和控制图分析传感器节点上的历史数据，提高对节点故障判断的灵敏度并且定位出异常时间点；然后，结合网络内邻居节点间的数据交换，通过判断节点的状态诊断出故障节点。实验结果表明，即使在整个网络中在节点故障率高达35%时，算法检测精度仍然高于97.7%，而误报率不超过2%。由此可见，在节点故障概率很高的情况下，此所提法也能得到很高的检测精度和较低的误报率，受节点故障率的影响明显减小。

关键词: 无线传感器网络, 故障诊断, 分布式, 累积和控制图, 中值绝对偏差

CLC Number:

TP393

LIU Qiuyue, CHENG Yong, WANG Jun, ZHONG Shuiming, XU Liya. Distributed fault detection for wireless sensor network based on cumulative sum control chart[J]. Journal of Computer Applications, 2016, 36(11): 3016-3020.

刘秋玥, 程勇, 王军, 钟水明, 徐利亚. 基于累积和控制图的分布式传感网络故障诊断[J]. 计算机应用, 2016, 36(11): 3016-3020.

References

[1] 马峻岩,周兴社,张羽,等.传感器网络调试研究综述[J].计算机学报,2012,35(3):405-422.(MA J Y, ZHOU X S, ZHANG Y, et al. Debugging sensor networks:a survey[J]. Chinese Journal of Computers, 2012, 35(3):405-422.)
[2] LI M, LIU Y, WANG J, et al. Sensor network navigation without locations[J].IEEE Transactions on Parallel & Distributed Systems, 2009, 24(7):2419-2427.
[3] MO L, HE Y, LIU Y, et al. Canopy closure estimates with GreenOrbs:sustainable sensing in the forest[C]//Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems. New York:ACM, 2009:99-112.
[4] WERNER-ALLEN G, DAWSON-HAGGERTY S, WELSH M. Lance:optimizing high-resolution signal collection in wireless sensor networks[C]//Proceedings of the 6th ACM Conference on Embedded Network Sensor Systems. New York:ACM, 2008:169-182.
[5] 李文锋,符修文.无线传感器网络抗毁性[J].计算机学报, 2015, 38(3):625-647.(LI W F, FU X W. Survey on invulnerability of wireless sensor networks[J]. Chinese Journal of Computers, 2015, 38(3):625-647.)
[6] RAMANATHAN N, SCHOELLHAMMER T, KOHLER E, et al. Suelo:human-assisted sensing for exploratory soil monitoring studies[C]//Proceedings of the 7th ACM Conference on Embedded Networked Sensor Systems. New York:ACM, 2009:197-210.
[7] LIU K, MA Q, GONG W, et al. Self-diagnosis for detecting system failures in large-scale wireless sensor networks[J]. IEEE Transactions on Wireless Communications, 2014, 13(10):5535-5545.
[8] CHEN J, KHER S, SOMANI A. Distributed fault detection of wireless sensor networks[C]//Proceedings of the 2006 Workshop on Dependability Issues in Wireless Ad Hoc Networks and Sensor Networks. New York:ACM, 2006:65-72.
[9] 高建良, 徐勇军, 李晓维.基于加权中值的分布式传感器网络故障检测[J].软件学报,2007, 18(5):1208-1217.(GAO J L, XU Y J, LI X W. Weighted-median based distributed fault detection for wireless sensor networks[J]. Journal of Software, 2007, 18(5):1208-1217.)
[10] LIN L, WANG H, DAI C. Fault diagnosis for wireless sensor network's node based on hamming neural network and rough set[C]//Proceedings of the 2008 IEEE Conference on Robotics, Automation and Mechatronics. Piscataway, NJ:IEEE, 2008:566-570.
[11] 董传明,刘克中,罗广,等.无线传感器网络环境下的一种轻量级事件容错检测算法[J].传感技术学报,2014,27(1):135-141.(DONG C M, LIU K Z, LUO G, et al. A light weight fault-tolerant event detection method in wireless sensor networks[J]. Chinese Journal of Sensors & Actuators, 2014, 27(1):135-141.)
[12] HAWKINS D M, OLWELL D H. Cumulative sum charts and charting for quality improvement[J]. Journal of the American Statistical Association, 2012, 94(1):107-107.
[13] YAO B, CHEN Q. On the temporal-spatial correlation based fault-tolerant dynamic event region detection scheme in wireless sensor networks[M]//Proceedings of the 3rd International Conference on Mobile Ad-Hoc and Sensor Networks. Berlin:Springer, 2007:511-523.
[14] ROUSSEEUW P J, CROUX C. Alternatives to the median absolute deviation[J]. Journal of the American Statistical Association, 1993, 88(424):1273-1283.

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Distributed fault detection for wireless sensor network based on cumulative sum control chart

基于累积和控制图的分布式传感网络故障诊断

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