College of Computer Science and Technology,HEU, Harbin, China

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Abstract—To solve the problem of distributed data streams clustering, the algorithm DB-DDSC (Density-Based Distribute Data Stream Clustering) was proposed. The algorithm consisted of two stages. First presented the concept of circular-point based on the representative points and designed the iterative algorithm to find the densityconnected circular-points, then generated the local model at the remote site. Second designed the algorithm to generate global clusters by combining the local models at coordinator site. The DB-DDSC algorithm can find the the clusters of different shapes under the distributed data stream environment, avoid frequently sending data by using the test-update algorithm, and reduce the data transmission. The experiments show that the DB-DDSC algorithm is feasible and scale expandable.

Index Terms—Data streams, data mining, clustering, distributed data stream.

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Cite: Bing Gao, Jianpei Zhang, "Density Based Distribute Data Stream Clustering Algorithm," Journal of Software vol. 8, no. 2, pp. 435-442, 2013.