Robustness of multipartite networks in face of random node failure

Zhaoxing Li and Li Chen

Chaos, Solitons & Fractals, 2019, vol. 121, issue C, 149-159

Abstract: Complex networks are prevalent in our lives. A complex network usually is composed of many components. Because the components of a network may suffer from random failures or intentional attacks, it is therefore important to study the robustness of networks in face of perturbations. Because real-world complex networks are practically interdependent, therefore many efforts have been made to investigate the robustness of interdependent or multilayer networks. Existing studies indicate that the robustness of multilayer networks displays first order phase transition, while the robustness of single layer networks only displays second order phase transition. Note that a simple form of a multilayer network is a multipartite network. Intuitively, the robustness of multipartite networks will also possess first order phase transition. In this paper we study the robustness of multipartite networks in face of random node failures. Extensive experiments have been carried out to test the robustness of multipartite networks whose degree distributions follow Poisson distribution. Interestingly, we have found that the robustness of multipartite networks displays second-order-like phase transition which is against the intuitive conclusion.

Keywords: Control networks; Multipartite networks; Network robustness; Phase transition (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (4)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:121:y:2019:i:c:p:149-159

DOI: 10.1016/j.chaos.2019.01.036

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