›› 2011, Vol. 26 ›› Issue (6): 942-953.doi: 10.1007/s11390-011-1191-y

• Computer Network and Internet • Previous Articles     Next Articles

An Efficient Method for Cleaning Dirty-Events over Uncertain Data in WSNs

Mo Chen1,2 (陈默), Student Member, CCF, ACM Ge Yu2, (于戈), Senior Member, CCF, Member, ACM, IEEE, Yu Gu2 (谷峪), Member, CCF, ACM Zi-Xi Jia2 (贾子熙), and Yan-Qiu Wang2 (王艳秋), Student Member, CCF, ACM   

  1. 1. Software College, Northeastern University, Shenyang 110004, China;
    2. College of Information Science and Engineering, Northeastern University, Shenyang 110004, China
  • Received:2010-04-16 Revised:2011-07-19 Online:2011-11-05 Published:2011-11-05
  • About author:Mo Chen received her B.S. and M.S. degrees in computer science from Northeastern University, China, in 2005 and 2007 respectively. She is currently a Ph.D. candidate in the Department of Computer Soft-ware and Theory, Northeastern Uni-versity. She is now an assistant lec-turer in Software College of North-eastern University. She is a student member of the CCF and member of the ACM. Her re-search interests include wireless sensor network and uncer-tain database.
    Ge Yu received his B.E. degree and M.E. degree in computer sci-ence from Northeastern University of China in 1982 and 1986, respectively, Ph.D. degree in computer science from Kyushu University of Japan in 1996. He has been a professor at Northeastern University since 1996. He is a member of the IEEE, ACM, and a senior member of the CCF. His research interests include database theory and technology, distributed and parallel systems, embedded software, and network information security.
    Yu Gu received his Ph.D. degree from the College of Information Sci-ence and Engineering, Northeastern University of China in 2010. He is an associate professor of Northeast-ern University, China. He is a mem-ber of the CCF and ACM. His major research interests include spatiotem-poral data management, RFID data management and data stream.
    Zi-Xi Jia received his Ph.D. de-gree in pattern recognition and in-telligent system from Northeastern University of China, in 2009. He is a lecturer in the Department of Computer Science and Technology of Northeastern University. His area of research is wireless sensor network.
    Yan-Qiu Wang received her B.S. and M.S. degrees in computer science from Northeastern Univer-sity, China, in 2007 and 2009 respec-tively. She is currently a Ph.D. can-didate at the Department of Com-puter Software and Theory, North-eastern University. She is a student member of the CCF and member of the ACM. Her research interests in-clude spatial temporal query and internet of things.
  • Supported by:

    tural Science Foundation of China under Grant Nos. 61003058, 60933001 and the Fundamental Research Funds for the Central Universities under Grant No. N090104001.

Event detection in wireless sensor networks (WSNs) has attracted much attention due to its importance in many applications. The erroneous abnormal data generated during event detection are prone to lead to false detection results. Therefore, in order to improve the reliability of event detection, we propose a dirty-event cleaning method based on spatio-temporal correlations among sensor data. Unlike traditional fault-tolerant approaches, our method takes into account the inherent uncertainty of sensor measurements and focuses on the type of directional events. A probability- based mapping scheme is introduced, which maps uncertain sensor data into binary data. Moreover, we give formulated definitions of transient dirty-event (TDE) and permanent dirty-event (PDE), which are cleaned by a novel fuzzy method and a collaborative cleaning scheme, respectively. Extensive experimental results show the effectiveness of our dirty-event cleaning method.

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