基于网络熵变率的节点重要性排序方法  

Node Importance Ranking Method Based on Network the Rate of Entropy Changes

作　　者：陈前 王昌达[1] CHEN Qian;WANG Changda(School of Computer Science and Communication Engineering,Jiangsu University,Zhenjiang 212013)

机构地区：[1]江苏大学计算机科学与通信工程学院,镇江212013

出　　处：《计算机与数字工程》2023年第5期1081-1085,1173,共6页Computer & Digital Engineering

基　　金：国家自然科学基金项目(编号:62072217,61672269)资助。

摘　　要：在通信网络中,节点的重要性不仅与网络的拓扑结构有关,而且与当前的网络负载状态相关。论文在分析网络负载和网络熵之间变化关系的基础上,首先定义了网络熵变率,然后设计了以网络熵变率为基础的节点重要性排序方法MixR(Mix Ranking)。论文以Abilene网和GEANT网的公开数据集作为分析对象,以SIR(Susceptible-Infected-Recovered)作为节点重要性评价的参考模型,通过与度中心性、接近中心性、特征向量中心性,以及半局部中心性方法对比,证实了MixR方法的有效性和准确性。In the communication network,the importance of nodes is not only related to the topology of the network,but also related to the current network load status.Based on the analysis of the relationship between network load change and network entropy changes,this paper puts forward the concept of network entropy change rate.On this basis,a further design of the node importance ranking method MixR(Mix Ranking)is proposed.Taking the public data sets of Abilene network and GEANT network as the analysis object,SIR(Susceptible-Infected-Recovered)is utilized the reference model for evaluation.Comparing to degree centrality,closeness centrality,eigenvector centrality and semi-local centrality,the results prove the effectiveness and accuracy of MixR.

关 键 词：网络熵 网络拓扑 节点重要性排序 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]