Robustness of scale-free networks with various parameters against cascading failures

Abstract

Many crucial real-world networks could be modeled as scale-free networks, which play an important role in the human society. Once these functional network systems suffer from cascading failures, they may lead to the malfunction of the rest part of networks. In recent years, the researches on cascading failures of scale-free networks have drawn great attention, and many studies focused on modeling the cascading phenomena and studying how to improve the robustness of networks against failures. However, the scale-free networks used in most existing studies are with fixed network parameters including scaling exponent and assortativity, which is segmentary for depicting the functionality of networked systems comprehensively. Therefore, in this paper, a series of generated scale-free networks with a certain range of parameters is adopted to evaluate the robustness against cascading failures. In addition, to make an accurate description of the ability of scale-free networks against cascading failures, we propose a link-based robustness index. The results show that influenced by the network structure, the enlargement of assortativity makes the networks weaker to resist node-based cascading failures, yet the impact on promoting link-based robustness is not clear enough. With higher scaling exponents, the tolerance of scale-free networks against link-based cascading failures decreases, however, it does not show obvious relation to node-based robustness.