{"title":"Robustness Evaluation of Multipartite Complex Networks Based on Percolation Theory","authors":"Qing Cai, S. Alam, Mahardhika Pratama, Jiming Liu","doi":"10.1109/TSMC.2019.2960156","DOIUrl":null,"url":null,"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.","PeriodicalId":55007,"journal":{"name":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","volume":"1995 1","pages":"6244-6257"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Systems Man and Cybernetics Part A-Systems and Humans","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSMC.2019.2960156","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 14
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.
期刊介绍:
The scope of the IEEE Transactions on Systems, Man, and Cybernetics: Systems includes the fields of systems engineering. It includes issue formulation, analysis and modeling, decision making, and issue interpretation for any of the systems engineering lifecycle phases associated with the definition, development, and deployment of large systems. In addition, it includes systems management, systems engineering processes, and a variety of systems engineering methods such as optimization, modeling and simulation.