Inverse Percolation to Quantify Robustness in Multiplex Networks
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 bee...
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| Main Authors: | , , , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2020-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2020/8796360 |
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| author | Edwin Montes-Orozco Roman-Anselmo Mora-Gutiérrez Bibiana Obregón-Quintana Sergio-G. de-los-Cobos-Silva Eric A. Rincón-García Pedro Lara-Velázquez Miguel A. Gutiérrez-Andrade |
| author_facet | Edwin Montes-Orozco Roman-Anselmo Mora-Gutiérrez Bibiana Obregón-Quintana Sergio-G. de-los-Cobos-Silva Eric A. Rincón-García Pedro Lara-Velázquez Miguel A. Gutiérrez-Andrade |
| author_sort | Edwin Montes-Orozco |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-37930a260fa14050926e61541fa398fa |
| institution | DOAJ |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2020-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-37930a260fa14050926e61541fa398fa2025-08-20T03:20:30ZengWileyComplexity1076-27871099-05262020-01-01202010.1155/2020/87963608796360Inverse Percolation to Quantify Robustness in Multiplex NetworksEdwin Montes-Orozco0Roman-Anselmo Mora-Gutiérrez1Bibiana Obregón-Quintana2Sergio-G. de-los-Cobos-Silva3Eric A. Rincón-García4Pedro Lara-Velázquez5Miguel A. Gutiérrez-Andrade6Posgrado en Ciencias y Tecnologías de la Información, Universidad Autónoma Metropolitana Iztapalapa, Mexico City, MexicoDepartamento de Sistemas, Universidad Autónoma Metropolitana Azcapotzalco, Mexico City, MexicoFacultad de Ciencias, Universidad Nacional Autónoma de México, Mexico City, MexicoDepartamento de Ingeniería Eléctrica, Universidad Autónoma Metropolitana Iztapalapa, Mexico City, MexicoDepartamento de Ingeniería Eléctrica, Universidad Autónoma Metropolitana Iztapalapa, Mexico City, MexicoDepartamento de Ingeniería Eléctrica, Universidad Autónoma Metropolitana Iztapalapa, Mexico City, MexicoDepartamento de Ingeniería Eléctrica, Universidad Autónoma Metropolitana Iztapalapa, Mexico City, MexicoInverse 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.http://dx.doi.org/10.1155/2020/8796360 |
| spellingShingle | Edwin Montes-Orozco Roman-Anselmo Mora-Gutiérrez Bibiana Obregón-Quintana Sergio-G. de-los-Cobos-Silva Eric A. Rincón-García Pedro Lara-Velázquez Miguel A. Gutiérrez-Andrade Inverse Percolation to Quantify Robustness in Multiplex Networks Complexity |
| title | Inverse Percolation to Quantify Robustness in Multiplex Networks |
| title_full | Inverse Percolation to Quantify Robustness in Multiplex Networks |
| title_fullStr | Inverse Percolation to Quantify Robustness in Multiplex Networks |
| title_full_unstemmed | Inverse Percolation to Quantify Robustness in Multiplex Networks |
| title_short | Inverse Percolation to Quantify Robustness in Multiplex Networks |
| title_sort | inverse percolation to quantify robustness in multiplex networks |
| url | http://dx.doi.org/10.1155/2020/8796360 |
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