无人机集群网络节点重要性的多属性决策  

Multi-Attribute Decision on the Importance of UAV Cluster Network Nodes

作　　者：左嘉娴 华翔[2] ZUO Jiaxian;HUA Xiang(School of Defence Science and Technology,Xi’an Technological University,Xi’an 710021,China;School of Electronic Information Engineering,Xi’an Technological University,Xi’an 710021,China)

机构地区：[1]西安工业大学兵器科学与技术学院,西安710021 [2]西安工业大学电子信息工程学院,西安710021

出　　处：《西安工业大学学报》2022年第4期422-426,共5页Journal of Xi’an Technological University

基　　金：陕西省重点研发计划项目(2020GY-073)。

摘　　要：针对无人机集群网络关键节点识别与保护问题,文中选取网络节点的局部属性、全局属性以及节点间的相关重要性等指标,通过变异系数法确定指标权重,基于多属性决策,提出了一种无人机集群网络节点重要性的评估算法。采用不同算法对ARPA网络节点重要性进行排序,以识别出ARPA网络重要节点。通过计算网络重要节点去除后所生成的子图数与子图最大规模,分析网络重要节点失效对网络连通性的破坏情况和分割情况。结果表明:相较于重要度评价矩阵法、信息熵法、贡献矩阵法等传统算法,多属性决策算法实现了ARPA网重要节点的有效识别,且识别性能优于传统算法,为无人机集群网络健壮性评估提供了新方法。In view of the identification and protection of key nodes of UAV cluster network,the local attributes,global attributes and relevant importance of network nodes are determined by the coefficient of variation method,and an evaluation algorithm for the importance of UAV cluster network nodes is proposed based on the multi-attribute decision.Different algorithms were used to rank the ARPA network nodes of importance to identify the important nodes of the ARPA network.We analyze the failure of network connectivity and segmentation by calculating the failure of important network nodes.The results show that compared with the traditional algorithms such as the importance evaluation matrix method,information entropy method and contribution matrix method,the multi-attribute decision algorithm realizes the effective identification of important nodes in the ARPA network,and the identification performance is better than the traditional algorithm,providing a new method for the UAV cluster network robustness evaluation.

关 键 词：无人机 集群网络 节点重要性 变异系数法 

分 类 号：TN929.5[电子电信—通信与信息系统]