Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/147383
Title: Robustness evaluation of multipartite complex networks based on percolation theory
Authors: Cai, Qing
Alam, Sameer
Pratama, Mahardhika
Liu, Jiming
Keywords: Engineering::Aeronautical engineering
Issue Date: 2020
Source: Cai, Q., Alam, S., Pratama, M. & Liu, J. (2020). Robustness evaluation of multipartite complex networks based on percolation theory. IEEE Transactions On Systems, Man, and Cybernatics: Systems. https://dx.doi.org/10.1109/TSMC.2019.2960156
Journal: IEEE Transactions on Systems, Man, and Cybernatics: Systems 
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.
URI: https://hdl.handle.net/10356/147383
ISSN: 2168-2216
DOI: 10.1109/TSMC.2019.2960156
Rights: © 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/TSMC.2019.2960156
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:ATMRI Journal Articles

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