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Self-Healing Networks: Redundancy and Structure

We introduce the concept of self-healing in the field of complex networks modelling; in particular, self-healing capabilities are implemented through distributed communication protocols that exploit redundant links to recover the connectivity of the system. We then analyze the effect of the level of...

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Detalles Bibliográficos
Autores principales: Quattrociocchi, Walter, Caldarelli, Guido, Scala, Antonio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3922772/
https://www.ncbi.nlm.nih.gov/pubmed/24533065
http://dx.doi.org/10.1371/journal.pone.0087986
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author Quattrociocchi, Walter
Caldarelli, Guido
Scala, Antonio
author_facet Quattrociocchi, Walter
Caldarelli, Guido
Scala, Antonio
author_sort Quattrociocchi, Walter
collection PubMed
description We introduce the concept of self-healing in the field of complex networks modelling; in particular, self-healing capabilities are implemented through distributed communication protocols that exploit redundant links to recover the connectivity of the system. We then analyze the effect of the level of redundancy on the resilience to multiple failures; in particular, we measure the fraction of nodes still served for increasing levels of network damages. Finally, we study the effects of redundancy under different connectivity patterns—from planar grids, to small-world, up to scale-free networks—on healing performances. Small-world topologies show that introducing some long-range connections in planar grids greatly enhances the resilience to multiple failures with performances comparable to the case of the most resilient (and least realistic) scale-free structures. Obvious applications of self-healing are in the important field of infrastructural networks like gas, power, water, oil distribution systems.
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spelling pubmed-39227722014-02-14 Self-Healing Networks: Redundancy and Structure Quattrociocchi, Walter Caldarelli, Guido Scala, Antonio PLoS One Research Article We introduce the concept of self-healing in the field of complex networks modelling; in particular, self-healing capabilities are implemented through distributed communication protocols that exploit redundant links to recover the connectivity of the system. We then analyze the effect of the level of redundancy on the resilience to multiple failures; in particular, we measure the fraction of nodes still served for increasing levels of network damages. Finally, we study the effects of redundancy under different connectivity patterns—from planar grids, to small-world, up to scale-free networks—on healing performances. Small-world topologies show that introducing some long-range connections in planar grids greatly enhances the resilience to multiple failures with performances comparable to the case of the most resilient (and least realistic) scale-free structures. Obvious applications of self-healing are in the important field of infrastructural networks like gas, power, water, oil distribution systems. Public Library of Science 2014-02-12 /pmc/articles/PMC3922772/ /pubmed/24533065 http://dx.doi.org/10.1371/journal.pone.0087986 Text en © 2014 Quattrociocchi et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Quattrociocchi, Walter
Caldarelli, Guido
Scala, Antonio
Self-Healing Networks: Redundancy and Structure
title Self-Healing Networks: Redundancy and Structure
title_full Self-Healing Networks: Redundancy and Structure
title_fullStr Self-Healing Networks: Redundancy and Structure
title_full_unstemmed Self-Healing Networks: Redundancy and Structure
title_short Self-Healing Networks: Redundancy and Structure
title_sort self-healing networks: redundancy and structure
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3922772/
https://www.ncbi.nlm.nih.gov/pubmed/24533065
http://dx.doi.org/10.1371/journal.pone.0087986
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