Department of Chemistry and Nanoscience, Ewha Womans University, Seoul, 03760, Republic of Korea.
Sci Rep. 2022 Jan 19;12(1):989. doi: 10.1038/s41598-021-04753-z.
In most cascading failure models in networks, overloaded nodes are assumed to fail and are removed from the network. However, this is not always the case due to network mitigation measures. Considering the effects of these mitigating measures, we propose a new cascading failure model that describes the probability that an overloaded node fails as a logistic function. By performing numerical simulations of cascading failures on Barabási and Albert (BA) scale-free networks and a real airport network, we compare the results of our model and the established model describing the probability of failure as a linear function. The simulation results show that the difference in the robustness of the two models depends on the initial load distribution and the redistribution of load. We further investigate the conditions of our new model under which the network exhibits the strongest robustness in terms of the load distribution and the network topology. We find the optimal value for the parameter of the load distribution and demonstrate that the robustness of the network improves as the average degree increases. The results regarding the optimal load distribution are verified by theoretical analysis. This work can be used to develop effective mitigation measures and design networks that are robust to cascading failure phenomena.
在大多数网络中的级联故障模型中，假设过载节点会失效并从网络中移除。然而，由于网络缓解措施的存在，情况并非总是如此。考虑到这些缓解措施的影响，我们提出了一种新的级联故障模型，该模型将过载节点失效的概率描述为逻辑函数。通过对 Barabási 和 Albert (BA) 无标度网络和真实机场网络上的级联故障进行数值模拟，我们比较了我们的模型和描述失效概率为线性函数的现有模型的结果。模拟结果表明，两种模型的稳健性差异取决于初始负载分布和负载再分配。我们进一步研究了我们的新模型在哪些条件下，根据负载分布和网络拓扑结构，网络表现出最强的稳健性。我们找到了负载分布参数的最优值，并证明了随着平均度数的增加，网络的稳健性会提高。通过理论分析验证了最优负载分布的结果。这项工作可用于开发有效的缓解措施和设计对级联故障现象具有鲁棒性的网络。
