Correlated network of networks enhances robustness against catastrophic failures.

Byungjoon Min,Muhua Zheng,Ming Tang

doi:10.1371/journal.pone.0195539

Byungjoon Min, Muhua Zheng + Show 1 more

Open Access

https://doi.org/10.1371/journal.pone.0195539

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Abstract

Networks in nature rarely function in isolation but instead interact with one another with a form of a network of networks (NoN). A network of networks with interdependency between distinct networks contains instability of abrupt collapse related to the global rule of activation. As a remedy of the collapse instability, here we investigate a model of correlated NoN. We find that the collapse instability can be removed when hubs provide the majority of interconnections and interconnections are convergent between hubs. Thus, our study identifies a stable structure of correlated NoN against catastrophic failures. Our result further suggests a plausible way to enhance network robustness by manipulating connection patterns, along with other methods such as controlling the state of node based on a local rule.

Highlights

Models of network of networks (NoN) may fall into three classes according to the functionality of interconnections: Modular NoN (M-NoN), Catastrophic NoN (C-NoN), and Robust NoN (R-NoN)
In this study we find that the collapse instabilities in C-NoN can be removed, and the model becomes stable by introducing correlated NoN
We first examine the robustness of NoN by changing the density of links in order to check the effect of outlinks

Summary

Introduction

Real-world complex systems ranging from critical infrastructure [1,2,3] and transportation networks [4, 5] to living organisms [6,7,8] are rarely formed by an isolated network but by a network of networks (NoN) [3, 8,9,10,11,12,13,14,15,16,17,18,19,20,21,22,23,24,25,26,27,28,29,30]. A node can be active only if any interconnected nodes in different networks belong to the global giant component. Such global rule results in an extreme instability of a system of networks since a small perturbation can trigger catastrophic collapse. A node in R-NoN model can be active even though interconnected nodes in a different network do not belong to the global giant component. With this modification, R-NoN model becomes robust but still maintains the functionality across different networks.

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Results

Discussion