Recovery Coupling in Multilayer Networks

TL;DR

This paper investigates how recovery processes in interconnected networks, like power and communication systems, influence overall resilience, revealing universal nonlinear recovery behaviors and introducing a theoretical framework to understand recovery coupling effects.

Contribution

It introduces a new theoretical framework for recovery coupling in multilayer networks and provides empirical evidence of its impact on system resilience.

Findings

Universal nonlinear recovery behavior observed in power grid failures

Recovery coupling significantly affects system resilience

Controlled experiments demonstrate recovery coupling's role beyond resource limitations

Abstract

The increased complexity of infrastructure systems has resulted in critical interdependencies between multiple networks---communication systems require electricity, while the normal functioning of the power grid relies on communication systems. These interdependencies have inspired an extensive literature on coupled multilayer networks, assuming that a component failure in one network causes failures in the other network, a hard interdependence that results in a cascade of failures across multiple systems. While empirical evidence of such hard coupling is limited, the repair and recovery of a network requires resources typically supplied by other networks, resulting in well documented interdependencies induced by the recovery process. If the support networks are not functional, recovery will be slowed. Here we collected data on the recovery time of millions of power grid failures, finding evidence of universal nonlinear behavior in recovery following large perturbations. We develop a theoretical framework to address recovery coupling, predicting quantitative signatures different from the multilayer cascading failures. We then rely on controlled natural experiments to separate the role of recovery coupling from other effects like resource limitations, offering direct evidence of how recovery coupling affects a system's functionality. The resulting insights have implications beyond infrastructure systems, offering insights on the fragility and senescence of biological systems.