一种特征加权模糊聚类的负载均衡算法

doi:10.3969/j.issn.1001-2400.2017.02.022

Abstract

Abstract:

Focusing on the data fusion problem of various loads, a fuzzy clustering based load balancing algorithm with feature weighted is proposed. First of all, various system resources are considered as dimensions for load metrics, and features for different dimensions are weighted so as to quantify comprehensive loads; then, this algorithm introduces fuzzy clustering, optimizes weight constraints, and adds penalty terms. Hence, the most suitable objective node cluster for load transferring is resolved through fuzzy clustering. Experimental results show that this algorithm can effectively fuse multidimensional load data and reduce standard deviation for node loads within the cluster by 21％ compared with existing algorithms.

Key words: load balancing, fuzzy clustering, feature weighted, object function, entropy

HUANG Weihua;MA Zhong;DAI Xinfa;XU Mingdi;GAO Yi;LIU Limin. Fuzzy clustering based load balancing algorithm with feature weighted[J].Journal of Xidian University, 2017, 44(2): 127-132.

References

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Fuzzy clustering based load balancing algorithm with feature weighted

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