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复杂网络中巨型连通分量的稳定性。

Stability of a giant connected component in a complex network.

机构信息

Department of Physics, Northeastern University, 110 Forsyth Street, 111 Dana Research Center, Boston, Massachusetts 02115, USA.

University of Virginia, Department of Systems and Information Engineering, Charlottesville, Virginia 22904, USA.

出版信息

Phys Rev E. 2018 Jan;97(1-1):012309. doi: 10.1103/PhysRevE.97.012309.

Abstract

We analyze the stability of the network's giant connected component under impact of adverse events, which we model through the link percolation. Specifically, we quantify the extent to which the largest connected component of a network consists of the same nodes, regardless of the specific set of deactivated links. Our results are intuitive in the case of single-layered systems: the presence of large degree nodes in a single-layered network ensures both its robustness and stability. In contrast, we find that interdependent networks that are robust to adverse events have unstable connected components. Our results bring novel insights to the design of resilient network topologies and the reinforcement of existing networked systems.

摘要

我们分析了网络巨型连通分量在不利事件影响下的稳定性,我们通过链路渗滤来模拟这些事件。具体来说,我们量化了网络最大连通分量中包含相同节点的程度,而不考虑特定的去活链路集。在单层系统的情况下,我们的结果是直观的:在单层网络中存在大量度节点,这既确保了网络的鲁棒性又确保了其稳定性。相比之下,我们发现对不利事件具有鲁棒性的相依网络具有不稳定的连通分量。我们的研究结果为弹性网络拓扑的设计和现有网络系统的加固提供了新的思路。

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