Emergence of robustness in networks of networks.
Emergence of robustness in networks of networks.
复制标题
网络网络中鲁棒性的出现。
DOI：
10.1103/physreve.95.062308
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发表时间：
2017
期刊：
影响因子：
--
通讯作者：
Makse,HernánA
中科院分区：
文献类型：
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作者：
Roth,Kevin;Morone,Flaviano;Min,Byungjoon;Makse,HernánA
网络的相互依赖网络（NONs）模型最近被引入[Proc. Natl]。学会科学。（美国）114,3849 (2017)PNASA60027-842410.1073/pnas。[1620808114]在大脑激活的背景下识别大脑NON中的神经集体影响者。在这里，我们研究了这种模型中鲁棒性的出现，并且我们开发了一种方法来推导出这种Erdös-Rényi NONs中随机渗透过渡的精确表达式。分析计算结果与数值模拟结果一致，并突出了NON对随机节点故障的鲁棒性，从而提出了一种新的鲁棒通用性NON类。这个鲁棒的NON模型的关键方面是，即使一个节点不属于巨大的相互连接的组件，它也可以被激活，从而允许NON从低于渗透阈值的地方构建，这在以前的相互依赖的网络模型中是不可能的。有趣的是，模型的阶段图揭示了NON最容易受到攻击的特定互连模式，从而标记了系统的鲁棒性随着依赖性连接的增加而提高的边界。
A model of interdependent networks of networks (NONs) was introduced recently [Proc. Natl. Acad. Sci. (USA) 114, 3849 (2017)PNASA60027-842410.1073/pnas.1620808114] in the context of brain activation to identify the neural collective influencers in the brain NON. Here we investigate the emergence of robustness in such a model, and we develop an approach to derive an exact expression for the random percolation transition in Erdös-Rényi NONs of this kind. Analytical calculations are in agreement with numerical simulations, and highlight the robustness of the NON against random node failures, which thus presents a new robust universality class of NONs. The key aspect of this robust NON model is that a node can be activated even if it does not belong to the giant mutually connected component, thus allowing the NON to be built from below the percolation threshold, which is not possible in previous models of interdependent networks. Interestingly, the phase diagram of the model unveils particular patterns of interconnectivity for which the NON is most vulnerable, thereby marking the boundary above which the robustness of the system improves with increasing dependency connections.