非齐次失效下相互依赖几何网络的鲁棒性

Khashayar Kamran, Jianan Zhang, E. Yeh, E. Modiano
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引用次数: 6

摘要

智能城市和智能电网等复杂系统严重依赖于它们相互依存的组成部分。一个网络中某个组件的故障可能会导致该支持组件在另一个网络中出现故障。支持大量相互依赖组件的组件可能更容易受到攻击和失败。本文研究了节点失效情况下两个相互依赖网络的鲁棒性问题。通过使用随机几何图(RGG)对每个网络进行建模,我们研究了非均匀节点失效后两个相互依赖的RGG的渗透条件。我们推导了相互依赖程度阈值(k1,k2)的解析界,使得相互依赖的RGGs在移除Gi中支持Gj (Vi, j _ {1,2},i≠j)中超过kj的节点后会渗透。我们使用数值模拟验证了该界,并表明在失效后k1和k2之间存在权衡以保持渗透。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Robustness of interdependent geometric networks under inhomogeneous failures
Complex systems such as smart cities and smart power grids rely heavily on their interdependent components. The failure of a component in one network may lead to the failure of the supported component in another network. Components which support a large number of interdependent components may be more vulnerable to attacks and failures. In this paper, we study the robustness of two interdependent networks under node failures. By modeling each network using a random geometric graph (RGG), we study conditions for the percolation of two interdependent RGGs after in-homogeneous node failures. We derive analytical bounds on the interdependent degree thresholds (k1,k2), such that the interdependent RGGs percolate after removing nodes in Gi that support more than kj nodes in Gj (Vi, j є {1,2},i ≠ j). We verify the bounds using numerical simulation, and show that there is a tradeoff between k1 and k2 for maintaining percolation after the failures.
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