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军事通信网络修复策略 被引量:3

Repair strategy of military communication network
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摘要 描述军事通信网络中节点遭受打击后的网络修复问题,采用网络加边的方法对通信网络的拓扑结构进行修复;建立以最大化网络抗毁性为目标函数,网络连接成本和网络连通为约束的增边修复模型;定义考虑冗余边和必须边的网络连接成本;设计基于离散人工蜂群算法的模型求解算法.通过具体的军事通信网络案例,在随机攻击和故意攻击2种典型攻击策略下进行仿真实验.在实验中,与随机加边、低度数加边以及低介数加边方法进行对比,结果表明采用所提出方法修复后的网络抗毁性更高,具有一定的优越性. The network repair problem after the nodes in the military communication network were hit was described,and the topology of the communication network was repaired by using the network edge-adding method.An edge addition repair model was established with maximizing network invulnerability as objective function,network connection cost and network connectivity as constraints.The network connection cost model considering redundant and necessary edges was defined.A model solving method based on the discrete artificial bee colony algorithm was proposed.Through specific cases of military communication network,simulation experiments were conducted under random and deliberate attacks,respectively.In the experiment,the proposed method was compared with other edge-adding methods,such as random addition,low degree first addition and low betweenness addition.Results showed that the proposed method can improve the survivability of network and the result was better than that of other three methods.
作者 陈冠宇 孙鹏 张杰勇 武君胜 CHEN Guan-yu;SUN Peng;ZHANG Jie-yong;WU Jun-sheng(College of Information and Navigation,Air Force Engineering University,Xi’an 710077,China;Unit 95816 of People’s Liberation Army,Hubei 432700,China;Department of Computer Science,Northwestern Polytechnical University,Xi’an 710072,China;Department of Software Micro-electronics,Northwestern Polytechnical University,Xi’an 710072,China)
出处 《浙江大学学报(工学版)》 EI CAS CSCD 北大核心 2019年第8期1536-1545,共10页 Journal of Zhejiang University:Engineering Science
基金 国家自然科学基金资助项目(61573017,61773396) 陕西省自然科学基金资助项目(2017JM6062) 装备预研重点实验室基金资助项目(61421010201)
关键词 军事通信网络 修复模型 修复策略 增边 离散人工蜂群算法 信息流 military communication network repair model repair strategy edge addition discrete artificial bee colony algorithm information flow
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