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Structural and spectral properties of generative models for synthetic multilayer air transportation networks

To understand airline transportation networks (ATN) systems we can effectively represent them as multilayer networks, where layers capture different airline companies, the nodes correspond to the airports and the edges to the routes between the airports. We focus our study on the importance of lever...

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Autores principales: Fügenschuh, Marzena, Gera, Ralucca, Méndez-Bermúdez, José Antonio, Tagarelli, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8530325/
https://www.ncbi.nlm.nih.gov/pubmed/34673801
http://dx.doi.org/10.1371/journal.pone.0258666
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author Fügenschuh, Marzena
Gera, Ralucca
Méndez-Bermúdez, José Antonio
Tagarelli, Andrea
author_facet Fügenschuh, Marzena
Gera, Ralucca
Méndez-Bermúdez, José Antonio
Tagarelli, Andrea
author_sort Fügenschuh, Marzena
collection PubMed
description To understand airline transportation networks (ATN) systems we can effectively represent them as multilayer networks, where layers capture different airline companies, the nodes correspond to the airports and the edges to the routes between the airports. We focus our study on the importance of leveraging synthetic generative multilayer models to support the analysis of meaningful patterns in these routes, capturing an ATN’s evolution with an emphasis on measuring its resilience to random or targeted attacks and considering deliberate locations of airports. By resorting to the European ATN and the United States ATN as exemplary references, in this work, we provide a systematic analysis of major existing synthetic generation models for ATNs, specifically ANGEL, STARGEN and BINBALL. Besides a thorough study of the topological aspects of the ATNs created by the three models, our major contribution lays on an unprecedented investigation of their spectral characteristics based on Random Matrix Theory and on their resilience analysis based on both site and bond percolation approaches. Results have shown that ANGEL outperforms STARGEN and BINBALL to better capture the complexity of real-world ATNs by featuring the unique properties of building a multiplex ATN layer by layer and of replicating layers with point-to-point structures alongside hub-spoke formations.
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spelling pubmed-85303252021-10-22 Structural and spectral properties of generative models for synthetic multilayer air transportation networks Fügenschuh, Marzena Gera, Ralucca Méndez-Bermúdez, José Antonio Tagarelli, Andrea PLoS One Research Article To understand airline transportation networks (ATN) systems we can effectively represent them as multilayer networks, where layers capture different airline companies, the nodes correspond to the airports and the edges to the routes between the airports. We focus our study on the importance of leveraging synthetic generative multilayer models to support the analysis of meaningful patterns in these routes, capturing an ATN’s evolution with an emphasis on measuring its resilience to random or targeted attacks and considering deliberate locations of airports. By resorting to the European ATN and the United States ATN as exemplary references, in this work, we provide a systematic analysis of major existing synthetic generation models for ATNs, specifically ANGEL, STARGEN and BINBALL. Besides a thorough study of the topological aspects of the ATNs created by the three models, our major contribution lays on an unprecedented investigation of their spectral characteristics based on Random Matrix Theory and on their resilience analysis based on both site and bond percolation approaches. Results have shown that ANGEL outperforms STARGEN and BINBALL to better capture the complexity of real-world ATNs by featuring the unique properties of building a multiplex ATN layer by layer and of replicating layers with point-to-point structures alongside hub-spoke formations. Public Library of Science 2021-10-21 /pmc/articles/PMC8530325/ /pubmed/34673801 http://dx.doi.org/10.1371/journal.pone.0258666 Text en https://creativecommons.org/publicdomain/zero/1.0/This is an open access article, free of all copyright, and may be freely reproduced, distributed, transmitted, modified, built upon, or otherwise used by anyone for any lawful purpose. The work is made available under the Creative Commons CC0 (https://creativecommons.org/publicdomain/zero/1.0/) public domain dedication.
spellingShingle Research Article
Fügenschuh, Marzena
Gera, Ralucca
Méndez-Bermúdez, José Antonio
Tagarelli, Andrea
Structural and spectral properties of generative models for synthetic multilayer air transportation networks
title Structural and spectral properties of generative models for synthetic multilayer air transportation networks
title_full Structural and spectral properties of generative models for synthetic multilayer air transportation networks
title_fullStr Structural and spectral properties of generative models for synthetic multilayer air transportation networks
title_full_unstemmed Structural and spectral properties of generative models for synthetic multilayer air transportation networks
title_short Structural and spectral properties of generative models for synthetic multilayer air transportation networks
title_sort structural and spectral properties of generative models for synthetic multilayer air transportation networks
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8530325/
https://www.ncbi.nlm.nih.gov/pubmed/34673801
http://dx.doi.org/10.1371/journal.pone.0258666
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