Robustness Evaluation of Multipartite Complex Networks Based on Percolation Theory

Qing Cai, Sameer Alam, Mahardhika Pratama, Jiming Liu

Research output: Contribution to journalArticlepeer-review

Abstract

To investigate the robustness of complex networks in face of disturbances can help prevent potential network disasters. Percolation on networks is a potent instrument for network robustness analysis. However, existing percolation theories are primarily developed for interdependent or multilayer networks. Little attention is paid to multipartite networks which are an indispensable part of complex networks. In this article, we theoretically explore the robustness of multipartite networks under node failures. We put forward the generic percolation theory for gauging the robustness of multipartite networks with arbitrary degree distributions. Our developed theory is capable of quantifying the robustness of multipartite networks under either random or target node attacks. Our theory unravels the second order phase transition phenomenon for multipartite networks. In order to verify the correctness of the proposed theory, simulations on computer generated multipartite networks have been carried out. The experiments demonstrate that the simulation results coincide quite well with that yielded by the proposed theory.
Original languageEnglish
Pages (from-to)6244-6257
Number of pages14
JournalIEEE Transactions on Systems, Man, and Cybernetics: Systems
Volume51
Issue number10
Early online date7 Jan 2020
DOIs
Publication statusPublished - Oct 2021

User-Defined Keywords

  • Complex networks
  • multipartite networks
  • network robustness
  • percolation
  • system control

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