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Mitigation of cascading failures in complex networks

Cascading failures in many systems such as infrastructures or financial networks can lead to catastrophic system collapse. We develop here an intuitive, powerful and simple-to-implement approach for mitigation of cascading failures on complex networks based on local network structure. We offer an al...

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Autores principales: Smolyak, Alex, Levy, Orr, Vodenska, Irena, Buldyrev, Sergey, Havlin, Shlomo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528121/
https://www.ncbi.nlm.nih.gov/pubmed/32999338
http://dx.doi.org/10.1038/s41598-020-72771-4
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author Smolyak, Alex
Levy, Orr
Vodenska, Irena
Buldyrev, Sergey
Havlin, Shlomo
author_facet Smolyak, Alex
Levy, Orr
Vodenska, Irena
Buldyrev, Sergey
Havlin, Shlomo
author_sort Smolyak, Alex
collection PubMed
description Cascading failures in many systems such as infrastructures or financial networks can lead to catastrophic system collapse. We develop here an intuitive, powerful and simple-to-implement approach for mitigation of cascading failures on complex networks based on local network structure. We offer an algorithm to select critical nodes, the protection of which ensures better survival of the network. We demonstrate the strength of our approach compared to various standard mitigation techniques. We show the efficacy of our method on various network structures and failure mechanisms, and finally demonstrate its merit on an example of a real network of financial holdings.
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spelling pubmed-75281212020-10-02 Mitigation of cascading failures in complex networks Smolyak, Alex Levy, Orr Vodenska, Irena Buldyrev, Sergey Havlin, Shlomo Sci Rep Article Cascading failures in many systems such as infrastructures or financial networks can lead to catastrophic system collapse. We develop here an intuitive, powerful and simple-to-implement approach for mitigation of cascading failures on complex networks based on local network structure. We offer an algorithm to select critical nodes, the protection of which ensures better survival of the network. We demonstrate the strength of our approach compared to various standard mitigation techniques. We show the efficacy of our method on various network structures and failure mechanisms, and finally demonstrate its merit on an example of a real network of financial holdings. Nature Publishing Group UK 2020-09-30 /pmc/articles/PMC7528121/ /pubmed/32999338 http://dx.doi.org/10.1038/s41598-020-72771-4 Text en © The Author(s) 2020 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Smolyak, Alex
Levy, Orr
Vodenska, Irena
Buldyrev, Sergey
Havlin, Shlomo
Mitigation of cascading failures in complex networks
title Mitigation of cascading failures in complex networks
title_full Mitigation of cascading failures in complex networks
title_fullStr Mitigation of cascading failures in complex networks
title_full_unstemmed Mitigation of cascading failures in complex networks
title_short Mitigation of cascading failures in complex networks
title_sort mitigation of cascading failures in complex networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7528121/
https://www.ncbi.nlm.nih.gov/pubmed/32999338
http://dx.doi.org/10.1038/s41598-020-72771-4
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