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Robustness of a Tree-like Network of Interdependent Networks

Published 29 Aug 2011 in physics.data-an, cs.SI, and physics.soc-ph | (1108.5515v1)

Abstract: In reality, many real-world networks interact with and depend on other networks. We develop an analytical framework for studying interacting networks and present an exact percolation law for a network of nn interdependent networks (NON). We present a general framework to study the dynamics of the cascading failures process at each step caused by an initial failure occurring in the NON system. We study and compare both nn coupled Erd\H{o}s-R\'{e}nyi (ER) graphs and nn coupled random regular (RR) graphs. We found recently [Gao et. al. arXive:1010.5829] that for an NON composed of nn ER networks each of average degree kk, the giant component, PP_{\infty}, is given by P=p[1exp(kP)]<sup>nP_{\infty}=p[1-\exp(-kP_{\infty})]<sup>n where $1-p$ is the initial fraction of removed nodes. Our general result coincides for n=1n=1 with the known Erd\H{o}s-R\'{e}nyi second-order phase transition at a threshold, p=pcp=p_c, for a single network. For n=2n=2 the general result for PP_{\infty} corresponds to the n=2n=2 result [Buldyrev et. al., Nature, 464, (2010)]. Similar to the ER NON, for n=1n=1 the percolation transition at pcp_c, is of second order while for any $n&gt;1$ it is of first order. The first order percolation transition in both ER and RR (for $n&gt;1$) is accompanied by cascading failures between the networks due to their interdependencies. However, we find that the robustness of nn coupled RR networks of degree kk is dramatically higher compared to the nn coupled ER networks of average degree kk. While for ER NON there exists a critical minimum average degree k=kmink=k_{\min}, that increases with nn, below which the system collapses, there is no such analogous kmink_{\min} for RR NON system.

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