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JACIII Vol.19 No.3 pp. 343-348
doi: 10.20965/jaciii.2015.p0343
(2015)

Paper:

The Research of the Distributed Resource-Aware K-means Clustering Algorithm

Xiaoni Wang

School of Applied Science, Beijing Information Science and Technology University
No.12, Qing He Xiao Ying East Road, Haidian District, Beijing, China

Received:
October 19, 2014
Accepted:
January 27, 2015
Online released:
May 20, 2015
Published:
May 20, 2015
Keywords:
distributed, resource-aware, clustering, adaptive, real-time
Abstract

According to the characteristics of the constrained resource in distributed real-time data mining in the Internet of Things (IOT) environment, a distributed data mining method is researched in such environment. Based on the limits of computing ability, storage ability, battery energy resources, network bandwidth, and the Internet single point failure, the distributed network data mining method is researched, and the adaptive technology and peer-to-peer node method are adopted. The DRA-Kmeans algorithm of data mining based on the K-means algorithm is proposed, and the amount of data communication among the sites to reduce the number of iterations and clustering is reduced. Clustering efficiency is improved, and better clustering results and execution efficiency are achieved.

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Last updated on Mar. 28, 2017