李永, 余镇危. 基于免疫克隆算法和K-medoids的网络节点聚类[J]. 微电子学与计算机, 2011, 28(8): 119-122.
引用本文: 李永, 余镇危. 基于免疫克隆算法和K-medoids的网络节点聚类[J]. 微电子学与计算机, 2011, 28(8): 119-122.
LI Yong, YU Zhen-wei. Network Nodes Clustering Based on Immune Clonal Algorithm and K-medoids[J]. Microelectronics & Computer, 2011, 28(8): 119-122.
Citation: LI Yong, YU Zhen-wei. Network Nodes Clustering Based on Immune Clonal Algorithm and K-medoids[J]. Microelectronics & Computer, 2011, 28(8): 119-122.

基于免疫克隆算法和K-medoids的网络节点聚类

Network Nodes Clustering Based on Immune Clonal Algorithm and K-medoids

  • 摘要: 在大规模分布式网络应用中,对网络节点进行聚类是构建高效网络体系结构的有效办法之一.在利用网络坐标系统Vivaldi得到各个节点的网络坐标的基础上,对网络节点进行K-medoids聚类.然后,针对K-medoids算法对初始中心选值敏感和易陷入局部极值的问题,提出基于免疫克隆算法的K-medoids聚类.实验结果表明,该聚类算法具有良好的可靠性及可扩展性,能对节点进行有效聚类.

     

    Abstract: In large-scale distributed network applications,nodes clustering is a useful way to construct an effective network infrastructure.The coordinates of network nodes can be get by the network coordinates system Vivaldi,then,network nodes can be clustered by the K-medoids algorithm according to their coordinates.But K-medoids is sensitive to the initial cluster centers and easy to get stuck at the local optimal solutions.In order to improve the performance of the K-medoids algorithm,the K-medoids based on immune clonal algorithm(KICA) is presented in this paper.Experimental results show KICA has good reliability and expansibility,and it is effective for clustering internet nodes.

     

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