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Failure and recovery in dynamical networks
Failure, damage spread and recovery crucially underlie many spatially embedded networked systems ranging from transportation structures to the human body. Here we study the interplay between spontaneous damage, induced failure and recovery in both embedded and non-embedded networks. In our model the...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5290536/ https://www.ncbi.nlm.nih.gov/pubmed/28155876 http://dx.doi.org/10.1038/srep41729 |
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author | Böttcher, L. Luković, M. Nagler, J. Havlin, S. Herrmann, H. J. |
author_facet | Böttcher, L. Luković, M. Nagler, J. Havlin, S. Herrmann, H. J. |
author_sort | Böttcher, L. |
collection | PubMed |
description | Failure, damage spread and recovery crucially underlie many spatially embedded networked systems ranging from transportation structures to the human body. Here we study the interplay between spontaneous damage, induced failure and recovery in both embedded and non-embedded networks. In our model the network’s components follow three realistic processes that capture these features: (i) spontaneous failure of a component independent of the neighborhood (internal failure), (ii) failure induced by failed neighboring nodes (external failure) and (iii) spontaneous recovery of a component. We identify a metastable domain in the global network phase diagram spanned by the model’s control parameters where dramatic hysteresis effects and random switching between two coexisting states are observed. This dynamics depends on the characteristic link length of the embedded system. For the Euclidean lattice in particular, hysteresis and switching only occur in an extremely narrow region of the parameter space compared to random networks. We develop a unifying theory which links the dynamics of our model to contact processes. Our unifying framework may help to better understand controllability in spatially embedded and random networks where spontaneous recovery of components can mitigate spontaneous failure and damage spread in dynamical networks. |
format | Online Article Text |
id | pubmed-5290536 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-52905362017-02-06 Failure and recovery in dynamical networks Böttcher, L. Luković, M. Nagler, J. Havlin, S. Herrmann, H. J. Sci Rep Article Failure, damage spread and recovery crucially underlie many spatially embedded networked systems ranging from transportation structures to the human body. Here we study the interplay between spontaneous damage, induced failure and recovery in both embedded and non-embedded networks. In our model the network’s components follow three realistic processes that capture these features: (i) spontaneous failure of a component independent of the neighborhood (internal failure), (ii) failure induced by failed neighboring nodes (external failure) and (iii) spontaneous recovery of a component. We identify a metastable domain in the global network phase diagram spanned by the model’s control parameters where dramatic hysteresis effects and random switching between two coexisting states are observed. This dynamics depends on the characteristic link length of the embedded system. For the Euclidean lattice in particular, hysteresis and switching only occur in an extremely narrow region of the parameter space compared to random networks. We develop a unifying theory which links the dynamics of our model to contact processes. Our unifying framework may help to better understand controllability in spatially embedded and random networks where spontaneous recovery of components can mitigate spontaneous failure and damage spread in dynamical networks. Nature Publishing Group 2017-02-03 /pmc/articles/PMC5290536/ /pubmed/28155876 http://dx.doi.org/10.1038/srep41729 Text en Copyright © 2017, The Author(s) http://creativecommons.org/licenses/by/4.0/ This work is licensed under a Creative Commons Attribution 4.0 International License. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in the credit line; if the material is not included under the Creative Commons license, users will need to obtain permission from the license holder to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ |
spellingShingle | Article Böttcher, L. Luković, M. Nagler, J. Havlin, S. Herrmann, H. J. Failure and recovery in dynamical networks |
title | Failure and recovery in dynamical networks |
title_full | Failure and recovery in dynamical networks |
title_fullStr | Failure and recovery in dynamical networks |
title_full_unstemmed | Failure and recovery in dynamical networks |
title_short | Failure and recovery in dynamical networks |
title_sort | failure and recovery in dynamical networks |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5290536/ https://www.ncbi.nlm.nih.gov/pubmed/28155876 http://dx.doi.org/10.1038/srep41729 |
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