Asymmetry in interdependence makes a multilayer system more robust against cascading failures

TL;DR

This paper investigates how asymmetry in interdependence between layers of multilayer networks influences their robustness against cascading failures, revealing that asymmetry can switch the nature of phase transitions and enhance resilience.

Contribution

It introduces a novel failure mechanism accounting for asymmetric interdependence and develops a theory to predict percolation transition points in multilayer networks.

Findings

Asymmetry causes a switch from first- to second-order phase transition.

Theoretical predictions match numerical results on synthetic and empirical networks.

Asymmetric interdependence can be used to design more resilient multilayer systems.

Abstract

Multilayer networked systems are ubiquitous in nature and engineering, and the robustness of these systems against failures is of great interest. A main line of theoretical pursuit has been percolation induced cascading failures, where interdependence between network layers is conveniently and tacitly assumed to be symmetric. In the real world, interdependent interactions are generally asymmetric. To uncover and quantify the impact of asymmetry in interdependence on network robustness, we focus on percolation dynamics in double-layer systems and implement the following failure mechanism: once a node in a network layer fails, the damage it can cause depends not only on its position in the layer but also on the position of its counterpart neighbor in the other layer. We find that the characteristics of the percolation transition depend on the degree of asymmetry, where the striking phenomenon of a switch in the nature of the phase transition from first- to second-order arises. We derive a theory to calculate the percolation transition points in both network layers, as well as the transition switching point, with strong numerical support from synthetic and empirical networks. Not only does our work shed light upon the factors that determine the robustness of multilayer networks against cascading failures, but it also provides a scenario by which the system can be designed or controlled to reach a desirable level of resilience.