Breakup of Directed Multipartite Networks

Qing Cai, Mahardhika Pratama, Sameer Alam, Chunyao Ma, Jiming Liu

Research output: Contribution to journalJournal articlepeer-review

6 Citations (Scopus)


A complex network in reality often consists of profuse components, which might suffer from unpredictable perturbations. Because the components of a network could be interdependent, therefore the failures of a few components may trigger catastrophes to the entire network. It is thus pivotal to exploit the robustness of complex networks. Existing studies on network robustness mainly deal with interdependent or multilayer networks; little work is done to investigate the robustness of multipartite networks, which are an indispensable part of complex networks. Here, we plumb the robustness of directed multipartite networks. To be specific, we exploit the robustness of bi-directed and unidirectional multipartite networks in face of random node failures. We, respectively, establish cascading and non-cascading models based on the largest connected component concept for depicting the dynamical processes on bi-directed and unidirectional multipartite networks subject to perturbations. Based on our developed models, we, respectively, derive the corresponding percolation theories for mathematically computing the robustness of directed multipartite networks subject to random node failures. We unravel the first-order and second-order phase transition phenomena on the robustness of directed multipartite networks. The correctness of our developed theories has been verified through experiments on computer-generated as well as real-world multipartite networks.

Original languageEnglish
Article number8620361
Pages (from-to)947-960
Number of pages14
JournalIEEE Transactions on Network Science and Engineering
Issue number3
Publication statusPublished - 1 Jul 2020

Scopus Subject Areas

  • Control and Systems Engineering
  • Computer Science Applications
  • Computer Networks and Communications

User-Defined Keywords

  • Complex networks
  • directed multipartite networks
  • network robustness
  • percolation


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