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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 and Tang, Yuan Yan 2016, The rationality of four metrics of network robustness: a viewpoint of robust growth of generalized meshes, PLoS One, vol. 11, no. 8, pp. 1-13, doi: 10.1371/journal.pone.0161077.

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Title The rationality of four metrics of network robustness: a viewpoint of robust growth of generalized meshes
Author(s) Yang, Xiaofan
Zhu, Yuanrui
Hong, Jing
Yang, Lu-xing
Wu, Yingbo
Tang, Yuan Yan
Journal name PLoS One
Volume number 11
Issue number 8
Article ID e0161077
Start page 1
End page 13
Total pages 13
Publisher Public Library of Science
Place of publication San Francisco, Calif.
Publication date 2016-08-12
ISSN 1932-6203
Keyword(s) Algorithms
Computer Simulation
Humans
Models, Statistical
Physiological Phenomena
Summary 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.
Language eng
DOI 10.1371/journal.pone.0161077
Field of Research MD Multidisciplinary
HERDC Research category C1.1 Refereed article in a scholarly journal
Copyright notice ©2016, Yang et al.
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30107773

Document type: Journal Article
Collections: School of Information Technology
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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.