Revisiting the Robustness of Complex Networks against Random Node Removal

Abstract

It is widely known that scale-free networks are robust against random node removal, which is one of major interesting findings in network science. This suggests that, for instance, communication networks such as the Internet is robust against random node failures caused by breakdowns and/or malicious attacks if their network topologies are scale-free networks. Generally, the ratio of failed devices (e.g., routers) to operational devices is not extremely high. In this paper, we revisit the robustness of complex networks against random node removal. Through simulations, we compare the robustness of scale-free and non-scale-free networks against random node removal as well as random edge removal. Our findings include that, contrary to common understanding, non-scale-free networks are more robust than scale-free networks except under extremely high node removal ratio. We also show that the robustness of non-scale-free networks can be further improved by bounding the minimum node degree of those networks.

Predictability of Network Robustness from Spectral Measures

“…In our previous works, we have revealed that non-scale-free networks are robust when the node removal ratio is low, whereas scale-free networks are robust when the node removal ratio is high [8]. Also depending on the node removal ratio, the superiority of a network in terms of robustness is different.…”

“…Since the robustness is a multifaceted property of a network, several different metrics for network robustness -those from geometrical viewpoints (e.g., the size of the largest connected component, the average path length, and the efficiency) [3], [6], [7], [8], [9], [10] as well as spectral viewpoints (e.g., spectral radius, natural connectivity, and algebraic connectivity) [11], [12], [13], [14] -have been proposed in the literature.…”