Efficient calculation of the robustness measure R for complex networks
In a recent work, Schneider et al. (2011) proposed a new measure R for network robustness, where the value of R is calculated within the entire process of malicious node attacks. In this paper, we present an approach to improve the calculation efficiency of R, in which a computationally efficient ro...
| Autores: | , , , , |
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| Formato: | artículo |
| Fecha de publicación: | 2017 |
| País: | España |
| Recursos: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2117/102283 |
| Acesso em linha: | https://hdl.handle.net/2117/102283 https://dx.doi.org/10.1016/j.physa.2017.02.054 |
| Access Level: | acceso abierto |
| Palavra-chave: | Network analysis (Planning) System analysis Network robustness Robustness measure Malicious attack Complex networks Anàlisi de xarxes (Planificació) Anàlisi de sistemes Àrees temàtiques de la UPC::Economia i organització d'empreses |
| Resumo: | In a recent work, Schneider et al. (2011) proposed a new measure R for network robustness, where the value of R is calculated within the entire process of malicious node attacks. In this paper, we present an approach to improve the calculation efficiency of R, in which a computationally efficient robustness measure R' is introduced when the fraction of failed nodes reaches to a critical threshold qc. Simulation results on three different types of network models and three real networks show that these networks all exhibit a computationally efficient robustness measure R'. The relationships between R' and the network size N and the network average degree <k> are also explored. It is found that the value of R' decreases with N while increases with <k>. Our results would be useful for improving the calculation efficiency of network robustness measure R for complex networks. |
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