Abstract
We propose DHCS, a method of distributed, hierarchical clustering and summarization for online data analysis and mining in sensor networks. Different from the acquisition and aggregation of raw sensory data, our method 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. Our simulation results on real world data sets as well as synthetic data sets show the effectiveness and efficiency of our approach.
This work is supported by the National Natural Science Foundation of China under Grant No.60473072, 60473051, and the National High Technology Development 863 Program of China under Grant No. 2006AA01Z230.
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Ma, X., Li, S., Luo, Q., Yang, D., Tang, S. (2007). Distributed, Hierarchical Clustering and Summarization in Sensor Networks. In: Dong, G., Lin, X., Wang, W., Yang, Y., Yu, J.X. (eds) Advances in Data and Web Management. APWeb WAIM 2007 2007. Lecture Notes in Computer Science, vol 4505. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-72524-4_20
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DOI: https://doi.org/10.1007/978-3-540-72524-4_20
Publisher Name: Springer, Berlin, Heidelberg
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