吉林大学学报(工学版) ›› 2010, Vol. 40 ›› Issue (06): 1639-1643.

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Improved clustering algorithm in peertopeer environments

TIAN Ye1,2,LIU Da-you1,2   

  1. 1.College of Computer Science and Technology,Jilin University,Changchun 130012,China;2.Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education,Jilin University,Changchun 130012,China
  • Received:2009-06-30 Online:2010-11-01 Published:2010-11-01

Abstract:

P2PKMeans algorithm is a distributed clustering algorithm in PeertoPeer (P2P) network. An improved data clustering algorithm, DKMeans, was proposed based on P2PKMeans algorithm. The proposed algorithm works in a localized asynchronous manner by communicating with the directly connected nodes without global synchronization. DKMeans decreases communication overhead of P2P network by saving cluster information of direct neighbors, thus reducing the total network communication cost. Compared with P2PKMeans, the traffic is much less using the proposed DKMeans and there is no degradation in accuracy. Furthermore, with the increase in nodes, the traffic growth rate of DKMeans is lower that of P2PKMeans.

Key words: artificial intelligence, K-Means algorithm, distributed data mining, P2P network

CLC Number: 

  • TP181
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