Abstract
Sensor networks are among the fastest growing technologies that have the potential of changing our lives drastically. These collaborative, dynamic and distributed computing and communicating systems are generating large amounts of data continuously. Finding useful patterns in large sensor data sets is a tempting however challenging task. In this paper, a clustering approach, CL2, CLuster and CLique, is proposed. CL2 can not only identify clusters in a multi-dimensional sensor dataset, discover the overall distribution patterns of the dataset, but also can be used for partitioning the sensor nodes into subgroups for task subdivision or energy management. CL2’s time efficiency, and accuracy of mining are evaluated through several experiments. A theoretic analysis of the algorithm is also presented.
This work is supported by the NKBRSF of China (973) under Grant No.G1999032705, the National ‘863’ High-Tech Program of China under Grant No.2002AA4Z3440.
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Ma, X., Li, S., Yang, D., Tang, S. (2004). CL2: A Multi-dimensional Clustering Approach in Sensor Networks. In: Wang, S., et al. Conceptual Modeling for Advanced Application Domains. ER 2004. Lecture Notes in Computer Science, vol 3289. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30466-1_22
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DOI: https://doi.org/10.1007/978-3-540-30466-1_22
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