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GDCluster: A general decentralized clustering algorithm

Mashayekhi, H ; Sharif University of Technology | 2015

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  1. Type of Document: Article
  2. DOI: 10.1109/TKDE.2015.2391123
  3. Publisher: IEEE Computer Society , 2015
  4. Abstract:
  5. In many popular applications like peer-to-peer systems, large amounts of data are distributed among multiple sources. Analysis of this data and identifying clusters is challenging due to processing, storage, and transmission costs. In this paper, we propose GDCluster, a general fully decentralized clustering method, which is capable of clustering dynamic and distributed data sets. Nodes continuously cooperate through decentralized gossip-based communication to maintain summarized views of the data set. We customize GDCluster for execution of the partition-based and density-based clustering methods on the summarized views, and also offer enhancements to the basic algorithm. Coping with dynamic data is made possible by gradually adapting the clustering model. Our experimental evaluations show that GDCluster can discover the clusters efficiently with scalable transmission cost, and also expose its supremacy in comparison to the popular method LSP2P
  6. Keywords:
  7. Clustering ; Density-based clustering ; Distributed systems ; Dynamic system ; Partition-based clustering
  8. Source: IEEE Transactions on Knowledge and Data Engineering ; Volume 27, Issue 7 , 2015 , Pages 1892-1905 ; 10414347 (ISSN)
  9. URL: http://ieeexplore.ieee.org/xpl/articleDetails.jsp?arnumber=7006742