The resilience of interdependent transportation networks under targeted attack

TL;DR

This paper investigates the resilience of interdependent transportation networks with flow dynamics under targeted attacks, revealing their extreme vulnerability compared to isolated networks.

Contribution

It extends existing models by incorporating flow considerations and analyzes how overload and interdependency failures affect network resilience.

Findings

Interdependent scale-free networks are highly vulnerable under attack.

Flow dynamics significantly reduce network resilience.

Vulnerability is greater than in non-flow or isolated network scenarios.

Abstract

Modern world builds on the resilience of interdependent infrastructures characterized as complex networks. Recently, a framework for analysis of interdependent networks has been developed to explain the mechanism of resilience in interdependent networks. Here we extend this interdependent network model by considering flows in the networks and study the system's resilience under different attack strategies. In our model, nodes may fail due to either overload or loss of interdependency. Under the interaction between these two failure mechanisms, it is shown that interdependent scale-free networks show extreme vulnerability. The resilience of interdependent SF networks is found in our simulation much smaller than single SF network or interdependent SF networks without flows.