边攻击下非对称相依作战网络级联失效模型

发布时间：2018-11-25 12:15

【摘要】：复杂网络理论在作战网络中的应用是一个全新的研究视角,也是探索网络结构和功能之间关系的有力手段.为研究负荷作用下相依作战网络的级联失效过程,首先依据军事系统的实际交联关系构建了非对称双层相依作战网络模型;然后改进了基于本地负荷重分配的非线性"负荷-容量"模型来研究连边的失效及负荷传递,计算了级联失效模型的计算复杂度;最后仿真分析了连边遭受蓄意攻击时,连边负荷及容量与网络级联抗毁性的关系,并与WS-WS对称网络模型进行对比.仿真结果表明:无论是孤立状态还是相依状态下,网络的级联抗毁性与连边容量变化呈正相关,而与负荷的变化呈负相关;相依网络的级联抗毁性比孤立网络要差,并且相依网络级联失效的过程更缓慢;孤立C2网络中的层级加权结构使得级联失效过程中出现短暂的平台期;与对称WS-WS相依网络相比,非对称作战网络的级联抗毁性更差.在非对称相依网络中,子网之间的级联抗毁性不同,而在相依对称网络中,子网的级联抗毁性几乎相同.
[Abstract]:The application of complex network theory in combat network is not only a new perspective, but also a powerful means to explore the relationship between network structure and function. In order to study the cascade failure process of dependent combat network under load, an asymmetric double-layer dependent combat network model is constructed according to the actual cross-linking relationship of military system. Then the nonlinear load-capacity model based on local load redistribution is improved to study the failure and load transfer of the connected edges, and the computational complexity of the cascade failure model is calculated. Finally, the relationship between the load and capacity of continuous edge and the network cascade invulnerability is analyzed and compared with the WS-WS symmetric network model. The simulation results show that the cascade invulnerability of the network is positively correlated with the capacity of the connected edge and negatively correlated with the change of the load, regardless of the isolated state or the dependent state. The cascade invulnerability of dependent networks is worse than that of isolated networks, and the cascade failure process of dependent networks is slower. The cascade invulnerability of asymmetric combat networks is worse than that of symmetric WS-WS dependent networks. In asymmetric dependent networks, the concatenated invulnerability of subnets is different, while in dependent symmetric networks, the concatenated invulnerability of subnets is almost the same.
【作者单位】：空军工程大学航空航天工程学院;武警工程大学信息工程系;
【基金】：陕西省科学技术研究发展项目(2013kjxx-82)
【分类号】：O157.5

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