Non-Markovian recovery makes complex networks more resilient against large-scale failures

Understanding failure propagation dynamics in complex networks with recovery processes is vital to realizing networks that are resistant to large scale failures. Here, the authors report a model for general failure propagation dynamics in complex networks with non-Markovian recovery processes.

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Autores principales:	Zhao-Hua Lin, Mi Feng, Ming Tang, Zonghua Liu, Chen Xu, Pak Ming Hui, Ying-Cheng Lai
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2020
Materias:	Science Q
Acceso en línea:	https://doaj.org/article/0e424b63766342c8a3c112330f24a760
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spelling	oai:doaj.org-article:0e424b63766342c8a3c112330f24a7602021-12-02T15:53:08ZNon-Markovian recovery makes complex networks more resilient against large-scale failures10.1038/s41467-020-15860-22041-1723https://doaj.org/article/0e424b63766342c8a3c112330f24a7602020-05-01T00:00:00Zhttps://doi.org/10.1038/s41467-020-15860-2https://doaj.org/toc/2041-1723Understanding failure propagation dynamics in complex networks with recovery processes is vital to realizing networks that are resistant to large scale failures. Here, the authors report a model for general failure propagation dynamics in complex networks with non-Markovian recovery processes.Zhao-Hua LinMi FengMing TangZonghua LiuChen XuPak Ming HuiYing-Cheng LaiNature PortfolioarticleScienceQENNature Communications, Vol 11, Iss 1, Pp 1-10 (2020)
institution	DOAJ
collection	DOAJ
language	EN
topic	Science Q
spellingShingle	Science Q Zhao-Hua Lin Mi Feng Ming Tang Zonghua Liu Chen Xu Pak Ming Hui Ying-Cheng Lai Non-Markovian recovery makes complex networks more resilient against large-scale failures
description	Understanding failure propagation dynamics in complex networks with recovery processes is vital to realizing networks that are resistant to large scale failures. Here, the authors report a model for general failure propagation dynamics in complex networks with non-Markovian recovery processes.
format	article
author	Zhao-Hua Lin Mi Feng Ming Tang Zonghua Liu Chen Xu Pak Ming Hui Ying-Cheng Lai
author_facet	Zhao-Hua Lin Mi Feng Ming Tang Zonghua Liu Chen Xu Pak Ming Hui Ying-Cheng Lai
author_sort	Zhao-Hua Lin
title	Non-Markovian recovery makes complex networks more resilient against large-scale failures
title_short	Non-Markovian recovery makes complex networks more resilient against large-scale failures
title_full	Non-Markovian recovery makes complex networks more resilient against large-scale failures
title_fullStr	Non-Markovian recovery makes complex networks more resilient against large-scale failures
title_full_unstemmed	Non-Markovian recovery makes complex networks more resilient against large-scale failures
title_sort	non-markovian recovery makes complex networks more resilient against large-scale failures
publisher	Nature Portfolio
publishDate	2020
url	https://doaj.org/article/0e424b63766342c8a3c112330f24a760
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Non-Markovian recovery makes complex networks more resilient against large-scale failures

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