CL2: A Multi-dimensional Clustering Approach in Sensor Networks

  • Xiuli Ma
  • Shuangfeng Li
  • Dongqing Yang
  • Shiwei Tang
Conference paper

DOI: 10.1007/978-3-540-30466-1_22

Part of the Lecture Notes in Computer Science book series (LNCS, volume 3289)
Cite this paper as:
Ma X., Li S., Yang D., Tang S. (2004) CL2: A Multi-dimensional Clustering Approach in Sensor Networks. In: Wang S. et al. (eds) Conceptual Modeling for Advanced Application Domains. ER 2004. Lecture Notes in Computer Science, vol 3289. Springer, Berlin, Heidelberg

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.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2004

Authors and Affiliations

  • Xiuli Ma
    • 1
    • 2
  • Shuangfeng Li
    • 1
  • Dongqing Yang
    • 1
  • Shiwei Tang
    • 1
    • 2
  1. 1.School of Electronics Engineering and Computer SciencePeking UniversityBeijingChina
  2. 2.National Laboratory on Machine PerceptionPeking UniversityBeijingChina

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