Journal of Computer Science and Technology

, Volume 26, Issue 4, pp 643–662 | Cite as

DHC: Distributed, Hierarchical Clustering in Sensor Networks

  • Xiu-Li Ma
  • Hai-Feng Hu
  • Shuang-Feng Li
  • Hong-Mei Xiao
  • Qiong Luo
  • Dong-Qing Yang
  • Shi-Wei Tang
Regular Paper


In many sensor network applications, it is essential to get the data distribution of the attribute value over the network. Such data distribution can be got through clustering, which partitions the network into contiguous regions, each of which contains sensor nodes of a range of similar readings. This paper proposes a method named Distributed, Hierarchical Clustering (DHC) for online data analysis and mining in senior networks. Different from the acquisition and aggregation of raw sensory data, DHC clusters sensor nodes based on their current data values as well as their geographical proximity, and computes a summary for each cluster. Furthermore, these clusters, together with their summaries, are produced in a distributed, bottom-up manner. The resulting hierarchy of clusters and their summaries facilitates interactive data exploration at multiple resolutions. It can also be used to improve the efficiency of data-centric routing and query processing in sensor networks. We also design and evaluate the maintenance mechanisms for DHC to make it be able to work on evolving data. Our simulation results on real world datasets as well as synthetic datasets show the effectiveness and efficiency of our approach.


clustering data mining wireless sensor networks 


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Supplementary material

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Copyright information

© Springer Science+Business Media, LLC & Science Press, China 2011

Authors and Affiliations

  • Xiu-Li Ma
    • 1
    • 2
  • Hai-Feng Hu
    • 1
    • 2
  • Shuang-Feng Li
    • 5
  • Hong-Mei Xiao
    • 1
    • 2
  • Qiong Luo
    • 4
  • Dong-Qing Yang
    • 1
    • 3
  • Shi-Wei Tang
    • 1
    • 2
  1. 1.School of Electronics Engineering and Computer SciencePeking UniversityBeijingChina
  2. 2.Key Laboratory of Machine Perception (Peking University), Ministry of EducationBeijingChina
  3. 3.Key Laboratory of High Confidence Software Technologies (Peking University), Ministry of EducationBeijingChina
  4. 4.Department of Computer Science and EngineeringHong Kong University of Science and Technology Clear Water BayKowloonHong Kong, China
  5. 5.Google ChinaBeijingChina

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