Inverse Percolation to Quantify Robustness in Multiplex Networks
Joint Authors
Montes-Orozco, Edwin
Mora-Gutiérrez, Roman-Anselmo
Obregón-Quintana, Bibiana
de-los-Cobos-Silva, Sergio-G.
Rincón-García, Eric A.
Lara-Velázquez, Pedro
Gutiérrez-Andrade, Miguel A.
Source
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-10-31
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Inverse percolation is known as the problem of finding the minimum set of nodes whose elimination of their links causes the rupture of the network.
Inverse percolation has been widely used in various studies of single-layer networks.
However, the use and generalization of multiplex networks have been little considered.
In this work, we propose a methodology based on inverse percolation to quantify the robustness of multiplex networks.
Specifically, we present a modified version of the mathematical model for the multiplex-vertex separator problem (m-VSP).
By solving the m-VSP, we can find nodes that cause the rupture of the mutually connected giant component (MCGC) and the large viable cluster (LVC) when their links are removed from the network.
The methodology presented in this work was tested in a set of benchmark networks, and as case study, we present an analysis using a set of multiplex social networks modeled with information about the main characteristics of the best universities in the world and the universities in Mexico.
The results show that the methodology presented in this work can work in different models and types of 2- and 3-layer multiplex networks without dividing the entire multiplex network into single-layer as some techniques described in the specific literature.
Furthermore, thanks to the fact that the technique does not require the calculation of some structural measure or centrality metric, and it is easy to scale for networks of different sizes.
American Psychological Association (APA)
Mora-Gutiérrez, Roman-Anselmo& Obregón-Quintana, Bibiana& de-los-Cobos-Silva, Sergio-G.& Rincón-García, Eric A.& Lara-Velázquez, Pedro& Gutiérrez-Andrade, Miguel A.…[et al.]. 2020. Inverse Percolation to Quantify Robustness in Multiplex Networks. Complexity،Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1144557
Modern Language Association (MLA)
Mora-Gutiérrez, Roman-Anselmo…[et al.]. Inverse Percolation to Quantify Robustness in Multiplex Networks. Complexity No. 2020 (2020), pp.1-11.
https://search.emarefa.net/detail/BIM-1144557
American Medical Association (AMA)
Mora-Gutiérrez, Roman-Anselmo& Obregón-Quintana, Bibiana& de-los-Cobos-Silva, Sergio-G.& Rincón-García, Eric A.& Lara-Velázquez, Pedro& Gutiérrez-Andrade, Miguel A.…[et al.]. Inverse Percolation to Quantify Robustness in Multiplex Networks. Complexity. 2020. Vol. 2020, no. 2020, pp.1-11.
https://search.emarefa.net/detail/BIM-1144557
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1144557