Gong Maoguo, Ma Lijia, Cai Qing, Jiao Licheng
Key Lab of Intelligent Perception and Image Understanding of Ministry of Education, International Research Center for Intelligent Perception and Computation, Xidian University, Xi'an, Shaanxi Province 710071, China.
Sci Rep. 2015 Feb 13;5:8439. doi: 10.1038/srep08439.
Coupled networks are extremely fragile because a node failure of a network would trigger a cascade of failures on the entire system. Existing studies mainly focused on the cascading failures and the robustness of coupled networks when the networks suffer from attacks. In reality, it is necessary to recover the damaged networks, and there are cascading failures in recovery processes. In this study, firstly, we analyze the cascading failures of coupled networks during recoveries. Then, a recovery robustness index is presented for evaluating the resilience of coupled networks to cascading failures in the recovery processes. Finally, we propose a technique aiming at protecting several influential nodes for enhancing robustness of coupled networks under the recoveries, and adopt six strategies based on the potential knowledge of network centrality to find the influential nodes. Experiments on three coupling networks demonstrate that with a small number of influential nodes protected, the robustness of coupled networks under the recoveries can be greatly enhanced.
耦合网络极其脆弱，因为网络中的一个节点故障会引发整个系统的一连串故障。现有研究主要关注网络遭受攻击时耦合网络的级联故障和鲁棒性。在现实中，有必要恢复受损网络，并且在恢复过程中存在级联故障。在本研究中，首先，我们分析耦合网络在恢复过程中的级联故障。然后，提出了一种恢复鲁棒性指标，用于评估耦合网络在恢复过程中对级联故障的恢复能力。最后，我们提出了一种旨在保护若干有影响力节点以增强耦合网络在恢复情况下鲁棒性的技术，并基于网络中心性的潜在知识采用六种策略来找到有影响力的节点。在三个耦合网络上进行的实验表明，通过保护少量有影响力的节点，可以大大提高耦合网络在恢复情况下的鲁棒性。
