A distributed K-means clustering algorithm in wireless sensor networks
Zhou J.2; Zhang Y.2; Jiang Y.1; Chen C.L.P.3; Chen L.3
2015-09-28
Conference NameInternational Conference on Informative and Cybernetics for Computational Social Systems (ICCSS)
Source PublicationICCSS 2015 - Proceedings: 2015 International Conference on Informative and Cybernetics for Computational Social Systems
Pages26-30
Conference DateAUG 13-15, 2015
Conference PlaceChengdu, PEOPLES R CHINA
Abstract

It is a hard work for the traditional k-means algorithm to perform data clustering in a large, dynamic distributed wireless sensor networks. In this paper, we propose a distributed k-means clustering algorithm, in which the distributed clustering is performed at each sensor with the collaboration of its neighboring sensors. To extract the important features and improve the clustering results, the attribute-weight-entropy regularization technique is used in the proposed clustering method. Experiments on synthetic datasets have shown the good performance of the proposed algorithms.

KeywordAttribute-weighted Clustering Distributed Clustering Wireless Sensor Networks
DOI10.1109/ICCSS.2015.7281143
URLView the original
Indexed BySCI
Language英语
WOS Research AreaComputer Science ; Engineering
WOS SubjectComputer Science, Cybernetics ; Engineering, Electrical & Electronic
WOS IDWOS:000380436700006
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Citation statistics
Cited Times [WOS]:9   [WOS Record]     [Related Records in WOS]
Document TypeConference paper
CollectionDEPARTMENT OF COMPUTER AND INFORMATION SCIENCE
Affiliation1.Hong Kong and Macao Affairs Office of the State Council
2.University of Jinan
3.Universidade de Macau
Recommended Citation
GB/T 7714
Zhou J.,Zhang Y.,Jiang Y.,et al. A distributed K-means clustering algorithm in wireless sensor networks[C],2015:26-30.
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