Perturbation: the Catastrophe Causer in Scale-Free Networks

TL;DR

This paper introduces a new model for cascading failures caused by perturbations, revealing that scale-free networks are more prone to catastrophic events than Euclidean lattices, and proposes a targeted safeguard strategy to mitigate such risks.

Contribution

The paper develops a novel perturbation-based model for network catastrophes and demonstrates the effectiveness of a targeted safeguard strategy in scale-free networks.

Findings

Catastrophes are more frequent in scale-free networks.

The severity of catastrophes is greater in scale-free networks.

Targeted safeguard strategies can reduce the impact of failures.

Abstract

A new model about cascading occurrences caused by perturbation is established to search after the mechanism because of which catastrophes in networks occur. We investigate the avalanche dynamics of our model on 2-dimension Euclidean lattices and scale-free networks and find out the avalanche dynamic behaviors is very sensitive to the topological structure of networks. The experiments show that the catastrophes occur much more frequently in scale-free networks than in Euclidean lattices and the greatest catastrophe in scale-free networks is much more serious than that in Euclidean lattices. Further more, we have studied how to reduce the catastrophes' degree, and have schemed out an effective strategy, called targeted safeguard-strategy for scale-free networks.