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一种非对称相依指控网络负载级联失效模型

A Load Cascading Failure Model for Asymmetric Dependent Command and Control Networks
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摘要 为探究指控网络遭受节点攻击时失效扩散的连锁反应过程,在非对称相依指控网络模型基础上,以节点综合重要度定义初始负载,运用容量-负载非线性模型计算节点容量,针对指控网络物理层和逻辑层各自特点,分别提出失效节点容量择优分配策略和非均匀负载可调重分配策略,构建了适于指控网络的级联失效模型,并运用数值仿真分析了各关键参数对指控网络级联失效抗毁性的影响。研究结果表明,容量裕度差异化参数与指控网络级联失效规模正相关,节点过载参数、负载分配系数与指控网络级联失效规模负相关;面对攻击,指控网络渗流失效、相依失效和过载失效相互叠加,网络更加脆弱;对比已有模型,所建模型能够更加有效地抑制级联失效传播,提高网络抗毁性。 To explore the chain reaction process of failure diffusion when a command and control(C2)network nodes are attacked,based on the asymmetric dependent C2 network model,the initial load is defined by the comprehensive importance of nodes,and the capacity load nonlinear model is used to calculate the node capacity.Based on the characteristics of the physical and logical layers of the C2 network,optimal allocation strategies for failed node capacity and non-uniform load adjustable reassignment strategies are proposed,respectively,a cascading failure model suitable for C2 networks is constructed,and tthe impact of key parameters on the invulnerability of cascading failures in C2 networks is analyzed using numerical simulation.The research results show that the capacity margin differentiation parameter is positively related to the cascade failure scale of C2 network,while the node overload parameter and load partition coefficient are negatively related;faced with attacks,accusing the network of seepage failure,dependent failure,and overload failure,the network becomes more fragile;compared with existing models,the constructed model can more effectively suppress cascading failure propagation and improve network invulnerability.
作者 岳地久 李建华 张杰勇 陈飞 YUE Dijiu;LI Jianhua;ZHANG Jieyong;CHEN Fei(Information and Navigation School,Air Force Engineering University,Xi'an 710077,China;PLA 94755 Troops,Zhangzhou 363000,China;PLA 94816 Troops,Fuzhou 350025,China)
出处 《现代防御技术》 北大核心 2024年第6期61-71,共11页 Modern Defence Technology
基金 全军军事类研究生重点资助课题(JY2022B010)。
关键词 指控网络 相依网络 级联失效 抗毁性 负载 模型 C2 network dependent network cascade failure invulnerability load model
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