The robustness of interdependent clustered networks

TL;DR

This paper develops an analytical method to study how clustering within interdependent networks affects their robustness, revealing that increased clustering significantly raises the vulnerability of the system to cascading failures.

Contribution

It introduces a new analytical approach based on Newman’s percolation method to assess the impact of clustering on interdependent network robustness.

Findings

Clustering increases the percolation threshold $p_c$, making networks more vulnerable.

Interdependent clustered networks are more susceptible to cascading failures.

The analytical model quantifies the effect of clustering on network robustness.

Abstract

It was recently found that cascading failures can cause the abrupt breakdown of a system of interdependent networks. Using the percolation method developed for single clustered networks by Newman [Phys. Rev. Lett. {\bf 103}, 058701 (2009)], we develop an analytical method for studying how clustering within the networks of a system of interdependent networks affects the system's robustness. We find that clustering significantly increases the vulnerability of the system, which is represented by the increased value of the percolation threshold $p_c$ in interdependent networks.