Optimal Network Robustness Against Attacks in Varying Degree Distributions

TL;DR

This paper investigates the optimal robustness of networks with varying degree distributions against targeted attacks, identifying random regular graphs as the most resilient structure under such conditions.

Contribution

It demonstrates that random regular graphs exhibit optimal robustness against targeted attacks in networks with varying degree distributions.

Findings

Random regular graphs have the highest robustness against targeted attacks.

Robustness is maximized when degree distribution variance is minimized.

Optimal robustness is achieved in networks with uniform degree distributions.

Abstract

In varying degree distributions, we investigate the optimally robust networks against targeted attacks to nodes with higher degrees. In considering that a network tends to have more robustness with a smaller variance of degree distributions, we clarify the optimal robustness at random regular graphs in their comprehensive discrete or random perturbations. By comparing robustness measurements on them, we find that random regular graphs have the optimal robustness against attacks in varying degree distributions.