Inter-similarity between coupled networks

TL;DR

This paper investigates how regular patterns of coupling, termed inter-similarity, between interdependent networks influence their robustness, revealing that higher inter-similarity enhances resilience to random failures.

Contribution

It introduces measures for inter-similarity and demonstrates that increased inter-similarity improves network robustness through simulations and real-world data analysis.

Findings

Higher inter-similarity correlates with increased robustness.

Inter-degree correlation and inter-clustering coefficient quantify inter-similarity.

Real-world port-airport network analysis confirms simulation results.

Abstract

Recent studies have shown that a system composed from several randomly interdependent networks is extremely vulnerable to random failure. However, real interdependent networks are usually not randomly interdependent, rather a pair of dependent nodes are coupled according to some regularity which we coin inter-similarity. For example, we study a system composed from an interdependent world wide port network and a world wide airport network and show that well connected ports tend to couple with well connected airports. We introduce two quantities for measuring the level of inter-similarity between networks (i) Inter degree-degree correlation (IDDC) (ii) Inter-clustering coefficient (ICC). We then show both by simulation models and by analyzing the port-airport system that as the networks become more inter-similar the system becomes significantly more robust to random failure.