基于桥接系数的指挥控制网络桥边识别方法
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摘要
桥边是网络结构连接的枢纽,在指挥控制网络信息流转中起着重要作用。针对指挥控制网络的桥边进行精准识别并加以保护,可提高指挥控制网络的抗毁性。为此,提出一种基于桥接系数的桥边识别方法。计算桥边的两端节点之间可达的二级和三级路径,根据两者之和与该边两端节点的增广度乘积之比定义桥接系数,并据此判断边的关键度。仿真结果表明,该方法与边介数方法识别出的桥边相似度超过50%,识别出73%的关键边能被Jaccard系数和边介数方法识别,利用边删除法验证桥边的关键度,其识别精度高于度乘积、Jaccard系数以及边介数方法。
The bridge-edge is the pivot of network structure connection and plays a crucial role in the flow of command and control network information.Accurately identifying and protecting the bridge edge can greatly improve the destruction resistance of the command and control network.To this end,a bridge-edge identification method based on bridging coefficient is proposed.The method calculates the sum of the number of reachable secondary and tertiary paths between the two endpoints of the key edge,calculate the ratio between the sum and the product of the augment degree of the endpoints to define bridging coefficient,and determine the criticality of edge.Simulation results show that the similarity between the bridge edges identified by the method and the betweenness method exceeds 50%,and 73% of the identified key edges can be identified by the Jaccard coefficient and the betweenness methods.Using the edge deletion method to verify the criticality of the bridge-edge,the recognition precision of the method is higher than those of the degree product,the Jaccard coefficient and the betweenness methods.
The bridge-edge is the pivot of network structure connection and plays a crucial role in the flow of command and control network information.Accurately identifying and protecting the bridge edge can greatly improve the destruction resistance of the command and control network.To this end,a bridge-edge identification method based on bridging coefficient is proposed.The method calculates the sum of the number of reachable secondary and tertiary paths between the two endpoints of the key edge,calculate the ratio between the sum and the product of the augment degree of the endpoints to define bridging coefficient,and determine the criticality of edge.Simulation results show that the similarity between the bridge edges identified by the method and the betweenness method exceeds 50%,and 73% of the identified key edges can be identified by the Jaccard coefficient and the betweenness methods.Using the edge deletion method to verify the criticality of the bridge-edge,the recognition precision of the method is higher than those of the degree product,the Jaccard coefficient and the betweenness methods.
引文
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[2] 孙昱,姚佩阳,张杰勇.C2组织信息结构效能测度及综合评估[J].系统工程与电子技术,2015,37(6):1313-1318.
[3] 刘俊.指挥控制网络连通可靠性建模与分析[D].成都:电子科技大学,2018.
[4] 崔文岩,孟相如,康巧燕,等.基于复合边权重的加权复杂网络级联抗毁性优化[J].系统工程与电子技术,2017,39(2):355-361.
[5] NEWMAN M E J.Fast algorithm for detecting community structure in networks[J].Physical Review E,2004,69(6):066133.
[6] 邱原,邢焕革.基于复杂理论的作战网络关键边评估方法[J].兵工自动化,2011,30(8):22-26.
[7] 韩忠明,陈炎,李梦琪,等.一种有效的基于三角结构的复杂网络节点影响力度量模型[J].物理学报,2016,65(16):1-12.
[8] 苏晓萍,宋玉蓉.利用邻域“结构洞”寻找社会网络中最具影响力节点[J].物理学报,2015,64(2).
[9] 陆晓静,宋玉蓉.基于边移除的智能电网级联故障鲁棒性分析[J].计算机工程,2018,44(1):292-298,305.
[10] WU Angkun,TIAN Liang,LIU Yangy.Bridges in complex networks[EB/OL].[2018-03-25].https://arxiv.org/pdf/1611.10159.pdf.
[11] 贾松卫.基于图论的复杂网络社团挖掘与结构分析[D].西安:西安电子科技大学,2016.
[12] 王玙,高琳.动态网络桥系数增量聚类算法[J].西安电子科技大学学报(自然科学版),2013,40(1):30-35.
[13] 王运明,王青野,潘成胜,等.面向结构洞的指挥控制网络关键节点识别方法[J].火力与指挥控制,2017,42(3):59-63.
[14] 陈世明,吕辉,徐青刚,等.基于度的正/负相关相依网络模型及其鲁棒性研究[J].物理学报,2015,64(4).
[15] WANG Yunming,CHEN Si,PAN Chengsheng,et al.Measure of invulnerability for command and control network based on mission link[J].Information Sciences,2018,426:148-159.