Research on the Robustness of Complex Networks Based on Dynamic Control of Node Redundancy Capacity
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摘要: 针对传统级联失效模型中冗余参数固定不变的问题，该文综合考虑节点受攻击程度不同和失效过程中网络拓扑的动态变化，建立了基于节点冗余容量动态控制(DRC)的级联失效模型。通过定义网络相变临界因子
$\theta $ 衡量节点失效引发级联失效的概率，分析了网络鲁棒性与$\theta $ 之间的相关性，并结合度分布函数详细推导了$\theta $ 的解析表达式，基于解析表达式提出了两种网络鲁棒性提升策略。仿真结果表明，在模型网络和真实网络中，根据被攻击节点度的不同，通过调整节点初始负载参数$\tau $ 可以有效提高目标网络的鲁棒性；DRC模型下级联失效传播范围较Motter-Lai(ML)模型显著减小。Abstract: In View of the problem of fixed redundancy parameters in the traditional cascade failure model, this paper comprehensively considers the different attack levels of nodes and the dynamic changes of the network topology during the failure process, and establishes a cascading failure model based on Dynamic control of node Redundancy Capacity (DRC). By defining the critical factor$\theta $ of the phase transition of the network to measure the probability of node failure leading to cascading failure, the correlation between network robustness and$\theta $ is analyzed, and the analytic expression of$\theta $ is derived in detail by combining degree distribution function, Based on analytic expressions, two network robustness enhancement strategies are proposed. The simulation results show that in model network and real network, the robustness of target network can be effectively improved by adjusting the initial load parameter$\tau $ of nodes according to the difference of degree of nodes under attack. The failure propagation range of DRC model is significantly reduced compared with Motter-Lai (ML) model.-
Key words:
- Complex networks /
- Cascade failure /
- Robustness /
- Node redundancy capacity
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