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The Rationality of Four Metrics of Network Robustness: A Viewpoint of Robust Growth of Generalized Meshes

There are quite a number of different metrics of network robustness. This paper addresses the rationality of four metrics of network robustness (the algebraic connectivity, the effective resistance, the average edge betweenness, and the efficiency) by investigating the robust growth of generalized m...

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Autores principales: Yang, Xiaofan, Zhu, Yuanrui, Hong, Jing, Yang, Lu-Xing, Wu, Yingbo, Tang, Yuan Yan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4982634/
https://www.ncbi.nlm.nih.gov/pubmed/27518448
http://dx.doi.org/10.1371/journal.pone.0161077
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author Yang, Xiaofan
Zhu, Yuanrui
Hong, Jing
Yang, Lu-Xing
Wu, Yingbo
Tang, Yuan Yan
author_facet Yang, Xiaofan
Zhu, Yuanrui
Hong, Jing
Yang, Lu-Xing
Wu, Yingbo
Tang, Yuan Yan
author_sort Yang, Xiaofan
collection PubMed
description There are quite a number of different metrics of network robustness. This paper addresses the rationality of four metrics of network robustness (the algebraic connectivity, the effective resistance, the average edge betweenness, and the efficiency) by investigating the robust growth of generalized meshes (GMs). First, a heuristic growth algorithm (the Proximity-Growth algorithm) is proposed. The resulting proximity-optimal GMs are intuitively robust and hence are adopted as the benchmark. Then, a generalized mesh (GM) is grown up by stepwise optimizing a given measure of network robustness. The following findings are presented: (1) The algebraic connectivity-optimal GMs deviate quickly from the proximity-optimal GMs, yielding a number of less robust GMs. This hints that the rationality of the algebraic connectivity as a measure of network robustness is still in doubt. (2) The effective resistace-optimal GMs and the average edge betweenness-optimal GMs are in line with the proximity-optimal GMs. This partly justifies the two quantities as metrics of network robustness. (3) The efficiency-optimal GMs deviate gradually from the proximity-optimal GMs, yielding some less robust GMs. This suggests the limited utility of the efficiency as a measure of network robustness.
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spelling pubmed-49826342016-08-29 The Rationality of Four Metrics of Network Robustness: A Viewpoint of Robust Growth of Generalized Meshes Yang, Xiaofan Zhu, Yuanrui Hong, Jing Yang, Lu-Xing Wu, Yingbo Tang, Yuan Yan PLoS One Research Article There are quite a number of different metrics of network robustness. This paper addresses the rationality of four metrics of network robustness (the algebraic connectivity, the effective resistance, the average edge betweenness, and the efficiency) by investigating the robust growth of generalized meshes (GMs). First, a heuristic growth algorithm (the Proximity-Growth algorithm) is proposed. The resulting proximity-optimal GMs are intuitively robust and hence are adopted as the benchmark. Then, a generalized mesh (GM) is grown up by stepwise optimizing a given measure of network robustness. The following findings are presented: (1) The algebraic connectivity-optimal GMs deviate quickly from the proximity-optimal GMs, yielding a number of less robust GMs. This hints that the rationality of the algebraic connectivity as a measure of network robustness is still in doubt. (2) The effective resistace-optimal GMs and the average edge betweenness-optimal GMs are in line with the proximity-optimal GMs. This partly justifies the two quantities as metrics of network robustness. (3) The efficiency-optimal GMs deviate gradually from the proximity-optimal GMs, yielding some less robust GMs. This suggests the limited utility of the efficiency as a measure of network robustness. Public Library of Science 2016-08-12 /pmc/articles/PMC4982634/ /pubmed/27518448 http://dx.doi.org/10.1371/journal.pone.0161077 Text en © 2016 Yang 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 (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Yang, Xiaofan
Zhu, Yuanrui
Hong, Jing
Yang, Lu-Xing
Wu, Yingbo
Tang, Yuan Yan
The Rationality of Four Metrics of Network Robustness: A Viewpoint of Robust Growth of Generalized Meshes
title The Rationality of Four Metrics of Network Robustness: A Viewpoint of Robust Growth of Generalized Meshes
title_full The Rationality of Four Metrics of Network Robustness: A Viewpoint of Robust Growth of Generalized Meshes
title_fullStr The Rationality of Four Metrics of Network Robustness: A Viewpoint of Robust Growth of Generalized Meshes
title_full_unstemmed The Rationality of Four Metrics of Network Robustness: A Viewpoint of Robust Growth of Generalized Meshes
title_short The Rationality of Four Metrics of Network Robustness: A Viewpoint of Robust Growth of Generalized Meshes
title_sort rationality of four metrics of network robustness: a viewpoint of robust growth of generalized meshes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4982634/
https://www.ncbi.nlm.nih.gov/pubmed/27518448
http://dx.doi.org/10.1371/journal.pone.0161077
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