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基于三角构成规则的加权有向网络拓扑生成算法
引用本文:苑文举,李飞鹏,孙鑫,付枫,刘衍珩.基于三角构成规则的加权有向网络拓扑生成算法[J].计算机应用,2011,31(3):591-593.
作者姓名:苑文举  李飞鹏  孙鑫  付枫  刘衍珩
作者单位:1. 长春工业大学 计算机科学与工程学院2. 吉林大学计算机科学与技术学院
基金项目:国家自然科学基金资助项目,吉林省信息产业发展专项资金资助项目
摘    要:针对加权无向图的网络拓扑模型难以表征真实网络环境下节点间有向性的问题,提出了基于三角构成规则的加权有向网络拓扑生成算法,依据概率优先选择节点的邻居节点进行有向性加边,通过网络边权的动态演化实现节点间的不对称性增长。并利用该算法进行了仿真实验。实验表明,基于三角构成的加权有向网络拓扑算法生成的网络拓扑结构符合真实环境下的网络拓扑结构所体现出来的拓扑特性,同时具有较好的聚类系数可控性。

关 键 词:加权有向网络  拓扑模型  三角构成规则  幂律分布  聚类系数  
收稿时间:2010-09-06
修稿时间:2010-11-03

Topology modeling algorithm for weighted directed network based on triad formation rule
YUAN Wen-ju,LI Fei-peng,SUN Xin,FU Feng,LIU Yan-heng.Topology modeling algorithm for weighted directed network based on triad formation rule[J].journal of Computer Applications,2011,31(3):591-593.
Authors:YUAN Wen-ju  LI Fei-peng  SUN Xin  FU Feng  LIU Yan-heng
Affiliation:1. College of Computer Science and Engineering, Changchun Polytechnic University, Changchun Jilin 130012, China2. College of Computer Science and Technology, Jilin University, Changchun Jilin 130012, China
Abstract:Topology generation algorithm of weighted directed network based on the triad formation rule was proposed. The directed edges were added to the network using weight preferential attachment rule and triad formation rule; moreover, the weights of network edges were evolved dynamically to realize the asymmetric interaction among nodes. The simulation results show that, the network topology, which is generated by the modeling algorithm for weighted directed network topology based on the triad formation rule, is consistent with topology characteristics showed by topology structures in the real network environment. Meanwhile, it has good controllability of the clustering coefficient.
Keywords:weighted directed network                                                                                                                        topology model                                                                                                                        triad formation rule                                                                                                                        power-law distribution                                                                                                                        clustering coefficient
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