摘要
针对目前网络仿真常用的Waxman随机网络拓扑模型存在的网络节点疏密不当、度数难以控制等问题,提出了一种基于K均值聚类的随机图拓扑生成算法KRT和一种基于K均值聚类的层次结构拓扑生成算法KHT。仿真实验表明使用基于K均值聚类的随机网络和层次结构拓扑生成器得到的网络拓扑图避免了两个节点间距离过近的情况发生,节点分布均匀且疏密得当,边的分布也比较均衡。
The nodes in Waxman random topology model is hard to control. A random topology generation algorithm based on K-means （KRT） and a hierarchic topology generation algorithm based on K-means （KHT） are presented. The simulation results shows that the network topology graph generated from KRT and KHT can avoid the occurrence of excessively near distance between two nodes, and make proper the nodes distribution uniformity and density, including the edges distribution.
出处
《通信技术》
2008年第9期110-112,共3页
Communications Technology
基金
国家"863"基金课题<大规模接入汇聚路由器(ACR)系统性能和关键技术研究>(2004AA103130)
