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An Efficient Method for Online Detecting Abnormal Cascading Pattern in Distributed Networks
Huang, Ting ; Ma, Xiuli ; Ji, Xiaokang ; Tang, Shiwei
2013
关键词abnormal cascading pattern correlation profile distributed network
英文摘要In many large-scale real-time monitoring applications, such as water quality monitoring of large water distribution networks, massive streams flow out of multiple concurrent sensors continuously. Online detection of abnormal event, especially of those spreading in the area, is vital to such networks, as the event will influence a large number of nodes once breaking out. In this paper, we first define such event as abnormal cascading pattern, and propose an efficient, online approach to detection. Instead of analyzing the streams independently, we focus on the correlation among streams and its variation. We first summarize the evolving correlation between each pair of streams into a profile, distinguish the abnormal variation based on the profile, and then catch the cascading pattern through associating the abnormal pairs. Experiments indicate high detection sensitivity, low false alarm rate and background noise tolerance of our approach.; http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000341633700126&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=8e1609b174ce4e31116a60747a720701 ; Computer Science, Artificial Intelligence; Computer Science, Information Systems; EI; CPCI-S(ISTP); 0
语种英语
DOI标识10.1109/FSKD.2013.6816293
内容类型其他
源URL[http://ir.pku.edu.cn/handle/20.500.11897/292481]  
专题信息科学技术学院
推荐引用方式
GB/T 7714
Huang, Ting,Ma, Xiuli,Ji, Xiaokang,et al. An Efficient Method for Online Detecting Abnormal Cascading Pattern in Distributed Networks. 2013-01-01.
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