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Uncovering the Dependence of Cascading Failures on Network Topology by Constructing Null Models
Cascading failures are the significant cause of network breakdowns in a variety of complex infrastructure systems. Given such a system, uncovering the dependence of cascading failures on its underlying topology is essential but still not well explored in the field of complex networks. This study off...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514463/ http://dx.doi.org/10.3390/e21111119 |
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author | Ding, Lin Liu, Si-Yuan Yang, Quan Xu, Xiao-Ke |
author_facet | Ding, Lin Liu, Si-Yuan Yang, Quan Xu, Xiao-Ke |
author_sort | Ding, Lin |
collection | PubMed |
description | Cascading failures are the significant cause of network breakdowns in a variety of complex infrastructure systems. Given such a system, uncovering the dependence of cascading failures on its underlying topology is essential but still not well explored in the field of complex networks. This study offers an original approach to systematically investigate the association between cascading failures and topological variation occurring in realistic complex networks by constructing different types of null models. As an example of its application, we study several standard Internet networks in detail. The null models first transform the original network into a series of randomized networks representing alternate realistic topologies, while taking its basic topological characteristics into account. Then considering the routing rule of shortest-path flow, it is sought to determine the implications of different topological circumstances, and the findings reveal the effects of micro-scale (such as degree distribution, assortativity, and transitivity) and meso-scale (such as rich-club and community structure) features on the cascade damage caused by deliberate node attacks. Our results demonstrate that the proposed method is suitable and promising to comprehensively analyze realistic influence of various topological properties, providing insight into designing the networks to make them more robust against cascading failures. |
format | Online Article Text |
id | pubmed-7514463 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75144632020-11-09 Uncovering the Dependence of Cascading Failures on Network Topology by Constructing Null Models Ding, Lin Liu, Si-Yuan Yang, Quan Xu, Xiao-Ke Entropy (Basel) Article Cascading failures are the significant cause of network breakdowns in a variety of complex infrastructure systems. Given such a system, uncovering the dependence of cascading failures on its underlying topology is essential but still not well explored in the field of complex networks. This study offers an original approach to systematically investigate the association between cascading failures and topological variation occurring in realistic complex networks by constructing different types of null models. As an example of its application, we study several standard Internet networks in detail. The null models first transform the original network into a series of randomized networks representing alternate realistic topologies, while taking its basic topological characteristics into account. Then considering the routing rule of shortest-path flow, it is sought to determine the implications of different topological circumstances, and the findings reveal the effects of micro-scale (such as degree distribution, assortativity, and transitivity) and meso-scale (such as rich-club and community structure) features on the cascade damage caused by deliberate node attacks. Our results demonstrate that the proposed method is suitable and promising to comprehensively analyze realistic influence of various topological properties, providing insight into designing the networks to make them more robust against cascading failures. MDPI 2019-11-15 /pmc/articles/PMC7514463/ http://dx.doi.org/10.3390/e21111119 Text en © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Ding, Lin Liu, Si-Yuan Yang, Quan Xu, Xiao-Ke Uncovering the Dependence of Cascading Failures on Network Topology by Constructing Null Models |
title | Uncovering the Dependence of Cascading Failures on Network Topology by Constructing Null Models |
title_full | Uncovering the Dependence of Cascading Failures on Network Topology by Constructing Null Models |
title_fullStr | Uncovering the Dependence of Cascading Failures on Network Topology by Constructing Null Models |
title_full_unstemmed | Uncovering the Dependence of Cascading Failures on Network Topology by Constructing Null Models |
title_short | Uncovering the Dependence of Cascading Failures on Network Topology by Constructing Null Models |
title_sort | uncovering the dependence of cascading failures on network topology by constructing null models |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7514463/ http://dx.doi.org/10.3390/e21111119 |
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