Network robustness of multiplex networks with interlayer degree correlations

TL;DR

This paper investigates how degree correlations between layers in multiplex networks influence their robustness, revealing that correlations can either enhance or weaken resilience depending on their nature and failure type.

Contribution

It introduces a generating function approach to analyze the impact of interlayer degree correlations on multiplex network robustness, highlighting diverse effects.

Findings

Maximally-correlated duplex networks are highly resilient to random failures.

Anti-correlated duplex networks resist targeted attacks but are vulnerable to random failures.

Correlations significantly influence the structural robustness of multiplex networks.

Abstract

We study the robustness properties of multiplex networks consisting of multiple layers of distinct types of links, focusing on the role of correlations between degrees of a node in different layers. We use generating function formalism to address various notions of the network robustness relevant to multiplex networks such as the resilience of ordinary- and mutual connectivity under random or targeted node removals as well as the biconnectivity. We found that correlated coupling can affect the structural robustness of multiplex networks in diverse fashion. For example, for maximally-correlated duplex networks, all pairs of nodes in the giant component are connected via at least two independent paths and network structure is highly resilient to random failure. In contrast, anti-correlated duplex networks are on one hand robust against targeted attack on high-degree nodes, but on the other hand they can be vulnerable to random failure.