Interdependency and Vulnerability of Multipartite Networks under Target Node Attacks
| Autor: | Mahardhika Pratama, Qing Cai, Sameer Alam |
|---|---|
| Přispěvatelé: | School of Computer Science and Engineering, School of Mechanical and Aerospace Engineering, Cai, Qing, Pratama, Mahardhika, Alam, Sameer |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: |
Theoretical computer science
Article Subject General Computer Science Computer science discontinuous phase transitions multilayer networks Multipartite Networks 01 natural sciences lcsh:QA75.5-76.95 010305 fluids & plasmas continuous phase transitions Robustness (computer science) 0103 physical sciences Target Node Attacks 010306 general physics Network model cascading failures Connected component Multidisciplinary Percolation (cognitive psychology) Node (networking) complex networks Complex network Cascading failure Multipartite node attacks Percolation Computer science and engineering [Engineering] percolation theories lcsh:Electronic computers. Computer science network robustness Centrality |
| Zdroj: | Complexity, Vol 2019 (2019) |
| ISSN: | 1099-0526 1076-2787 |
| Popis: | usc Refereed/Peer-reviewed Complex networks in reality may suffer from target attacks which can trigger the breakdown of the entire network. It is therefore pivotal to evaluate the extent to which a network could withstand perturbations. The research on network robustness has proven as a potent instrument towards that purpose. The last two decades have witnessed the enthusiasm on the studies of network robustness. However, existing studies on network robustness mainly focus on multilayer networks while little attention is paid to multipartite networks which are an indispensable part of complex networks. In this study, we investigate the robustness of multipartite networks under intentional node attacks. We develop two network models based on the largest connected component theory to depict the cascading failures on multipartite networks under target attacks. We then investigate the robustness of computer-generated multipartite networks with respect to eight node centrality metrics. We discover that the robustness of multipartite networks could display either discontinuous or continuous phase transitions. Interestingly, we discover that larger number of partite sets of a multipartite network could increase its robustness which is opposite to the phenomenon observed on multilayer networks. Our findings shed new lights on the robust structure design of complex systems. We finally present useful discussions on the applications of existing percolation theories that are well studied for network robustness analysis to multipartite networks. We show that existing percolation theories are not amenable to multipartite networks. Percolation on multipartite networks still deserves in-depth efforts. |
| Databáze: | OpenAIRE |
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