吉林大学学报(工学版) ›› 2015, Vol. 45 ›› Issue (3): 926-931.doi: 10.13229/j.cnki.jdxbgxb201503035

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IOT node load balancing strategy based on classification optimization

ZHAO Dong1, 2, HAN Xiao-yan3, ZHAO Hong-wei1, YU Fan-hua2   

  1. 1.College of Computer Science and Technology, Jilin University,Changchun 130022,China;
    2.College of Computer Science and Technology, Changchun Normal University, Changchun 130032, China;
    3.College of Information Technology, Jilin Agricultural University,Changchun 130118,China
  • Received:2014-04-15 Online:2015-05-01 Published:2015-05-01

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Abstract: The dynamic multi-factor combinations and k-Nearest Neighbor (KNN) classification method are adopted to designedly and in-depth analyze each node terminal. The feature nodes are classified according to their similarities. According to the classification strategy the usages of all nodes are organically sorted. The priority is given to the nodes of high usage efficiency and the easily idle device nodes, thus, to realize the network load balancing. Experiment results show that the proposed method can greatly improve the acceleration ratio, expansion ratio and data expansion rate.

Key words: computer application, classification analysis, node optimization, KNN, dynamic multiple factors combination

CLC Number: 

  • TP393
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