Cavity-based robustness analysis of interdependent networks: Influences of intranetwork and internetwork degree-degree correlations

TL;DR

This paper introduces a cavity method-based approach to analyze the robustness of interdependent networks, emphasizing how degree-degree correlations within and between networks influence their resilience to attacks and failures.

Contribution

The paper develops a novel cavity method framework that incorporates degree-degree correlations to assess interdependent network robustness, extending traditional generating function approaches.

Findings

Degree-degree correlations significantly affect robustness against targeted attacks.

Correlations have a minor impact on resilience to random failures.

The methodology aligns well with numerical experiments.

Abstract

We develop a methodology for analyzing the percolation phenomena of two mutually coupled (interdependent) networks based on the cavity method of statistical mechanics. In particular, we take into account the influence of degree-degree correlations inside and between the networks on the network robustness against targeted attacks and random failures. We show that the developed methodology is reduced to the well-known generating function formalism in the absence of degree-degree correlations. The validity of the developed methodology is confirmed by a comparison with the results of numerical experiments. Our analytical results imply that the robustness of the interdependent networks depends considerably on both the intra- and internetwork degree-degree correlations in the case of targeted attacks, whereas the significance of the degree-degree correlations is relatively low for random failures.