標題: Multidimensional Sensor Data Analysis in Cyber-Physical System: An Atypical Cube Approach
作者: Tang, Lu-An
Yu, Xiao
Kim, Sangkyum
Han, Jiawei
Peng, Wen-Chih
Sun, Yizhou
Leung, Alice
La Porta, Thomas
交大名義發表
National Chiao Tung University
公開日期: 2012
摘要: Cyber-Physical System (CPS) is an integration of distributed sensor networks with computational devices. CPS claims many promising applications, such as traffic observation, battlefield surveillance, and sensor-network-based monitoring. One important topic in CPS research is about the atypical event analysis, that is, retrieving the events from massive sensor data and analyzing them with spatial, temporal, and other multidimensional information. Many traditional methods are not feasible for such analysis since they cannot describe the complex atypical events. In this paper, we propose a novel model of atypical cluster to effectively represent such events and efficiently retrieve them from massive data. The basic cluster is designed to summarize an individual event, and the macrocluster is used to integrate the information from multiple events. To facilitate scalable, flexible, and online analysis, the atypical cube is constructed, and a guided clustering algorithm is proposed to retrieve significant clusters in an efficient manner. We conduct experiments on real sensor datasets with the size of more than 50 GB; the results show that the proposed method can provide more accurate information with only 15% to 20% time cost of the baselines.
URI: http://hdl.handle.net/11536/16374
http://dx.doi.org/724846
ISSN: 1550-1329
DOI: 724846
期刊: INTERNATIONAL JOURNAL OF DISTRIBUTED SENSOR NETWORKS
顯示於類別:期刊論文


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  1. 000304950100001.pdf