拓扑结构对网络承载能力的影响  

Influence of network topology on network capacity

作　　者：孙磊[1] 李荣[2] 靳聪[1] 陈孝国[3] 

机构地区：[1]中国矿业大学力学与建筑工程学院,北京100083 [2]浙江商业职业技术学院财金学院,杭州310053 [3]黑龙江科技大学理学院,哈尔滨150022

出　　处：《科技导报》2015年第1期86-89,共4页Science & Technology Review

基　　金：黑龙江省教育厅科学技术研究项目(12531577);黑龙江科技大学青年才俊培养计划项目(20120501)

摘　　要：通过建立3种典型的复杂网络模型及对应的输运模型,数值计算并仿真试验拓扑结构指标和网络承载能力的变化。结果显示:3种网络承载能力的数值计算结果和仿真试验结果基本吻合;核心节点的存在使得无标度网络的节点最大介数值所占比重高于其他网络,导致网络的承载能力最小;随机网络的节点最大介数值所占比重低于其他网络,导致承载能力最大;随着平均度的增大,各类型网络承载能力增加明显,但各种拓扑结构指标对承载能力提升的贡献不同。Three typical complex network models and corresponding traffic routing models were established to carry out numerical computation and simulation of topological indicators and network capacity,and empirical analysis of how network capacity is influenced by network topology was conducted. The results show that numerical calculation results and experimental results of the capacity of three different networks were roughly consistent. With existence of the core node,scale-free network had the shortest average travel path,and the proportion of the largest betweenness was much higher than that in other networks,leading to minimum capacity of the scale-free network; the proportion of the largest betweenness of nodes in random network was lower than that in other networks,leading to maximum capacity of the random network. The increase of average degree resulted in significant increase of network capacity,but the contribution of different topological indicators was not the same. Understanding the quantitative relation between network topology and network capacity is beneficial to conducting effective prevention and intervention concerning dynamic processes in the network.

关 键 词：复杂网络 承载能力 仿真 拓扑结构 

分 类 号：N941.4[自然科学总论—系统科学] O157.5[理学—数学]