郑玉霞, 蒋沅, 洪成. 基于时滞的复杂网络级联失效与恢复研究[J]. 南昌航空大学学报(自然科学版), 2025, 39(2): 19-29, 100. DOI: 10.3969/j.issn.2096-8566.2025.02.003
引用本文: 郑玉霞, 蒋沅, 洪成. 基于时滞的复杂网络级联失效与恢复研究[J]. 南昌航空大学学报(自然科学版), 2025, 39(2): 19-29, 100. DOI: 10.3969/j.issn.2096-8566.2025.02.003
Yuxia ZHENG, Yuan JIANG, Cheng HONG. Research on Cascading Failure and Recovery of Complex Networks Based on Time Delay[J]. Journal of nanchang hangkong university(Natural science edition), 2025, 39(2): 19-29, 100. DOI: 10.3969/j.issn.2096-8566.2025.02.003
Citation: Yuxia ZHENG, Yuan JIANG, Cheng HONG. Research on Cascading Failure and Recovery of Complex Networks Based on Time Delay[J]. Journal of nanchang hangkong university(Natural science edition), 2025, 39(2): 19-29, 100. DOI: 10.3969/j.issn.2096-8566.2025.02.003

基于时滞的复杂网络级联失效与恢复研究

Research on Cascading Failure and Recovery of Complex Networks Based on Time Delay

  • 摘要: 针对复杂网络的级联失效与恢复问题,本文提出一种基于时滞的复杂网络级联失效模型。该模型考虑级联失效过程中负载传播的损耗特性,以及邻居节点负载冗余量对时滞的影响,并明确定义节点失效时滞和负载传播损耗2个概念。同时,提出一种与失效进程同步的快速恢复策略,以增强网络的抗毁性和鲁棒性。在BA无标度网络、WS小世界网络、ER随机网络和NC最近邻网络4种典型网络上进行仿真实验,结果表明:负载传播损耗能有效延缓网络的级联失效进程;所提出的快速恢复策略可显著抑制网络崩溃;且随着负载的传播损耗参数和容忍系数的增大,网络的恢复能力与鲁棒性均得到明显提升。这些发现可为理解和控制实际基础设施网络中的级联故障现象提供重要的理论依据和实践指导。

     

    Abstract: To study the cascading failure and recovery problem of complex networks based on time delay, a time delay based cascading failure model is constructed. The model takes into account the loss characteristics of load propagation in the process of cascading failure and the influence of load redundancy of neighbor nodes on time delay, and clearly defines two concepts of node failure time delay and load propagation loss. At the same time, a fast recovery strategy synchronized with the failed process is proposed to improve the network's resilience and robustness. Simulation studies are conducted on four different typical networks: BA scale-free network, WS small-world network, ER random network and NC the nearest neighbor coupled network. The results show that load propagation loss can effectively delay the cascading failure process of the network, while fast recovery strategies can effectively prevent the network from collapsing. In addition, with the increase of load propagation loss parameters and tolerance coefficients, the recovery ability and robustness of the network during the recovery process are enhanced. These findings can provide important theoretical basis and practical guidance for understanding and controlling cascading fault phenomena in actual infrastructure networks.

     

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