Robustness surfaces of complex networks

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dc.contributor.author Manzano, Marc
dc.contributor.author Sahneh, Faryad D.
dc.contributor.author Scoglio, Caterina M.
dc.contributor.author Calle, Eusebi
dc.contributor.author Marzo Lazaro, Jose Luis
dc.date.accessioned 2014-11-25T20:28:27Z
dc.date.available 2014-11-25T20:28:27Z
dc.date.issued 2014-11-25
dc.identifier.uri http://hdl.handle.net/2097/18752
dc.description.abstract Despite the robustness of complex networks has been extensively studied in the last decade, there still lacks a unifying framework able to embrace all the proposed metrics. In the literature there are two open issues related to this gap: (a) how to dimension several metrics to allow their summation and (b) how to weight each of the metrics. In this work we propose a solution for the two aforementioned problems by defining the R*-value and introducing the concept of robustness surface (Ω). The rationale of our proposal is to make use of Principal Component Analysis (PCA). We firstly adjust to 1 the initial robustness of a network. Secondly, we find the most informative robustness metric under a specific failure scenario. Then, we repeat the process for several percentage of failures and different realizations of the failure process. Lastly, we join these values to form the robustness surface, which allows the visual assessment of network robustness variability. Results show that a network presents different robustness surfaces (i.e., dissimilar shapes) depending on the failure scenario and the set of metrics. In addition, the robustness surface allows the robustness of different networks to be compared. en_US
dc.language.iso en_US en_US
dc.relation.uri http://www.nature.com/srep/2014/140902/srep06133/pdf/srep06133.pdf en_US
dc.rights This work is licensed under a Creative Commons Attribution-NonCommercialNoDerivs 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 in order to reproduce the material. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject Applied mathematics en_US
dc.subject Phase transitions and critical phenomena en_US
dc.subject Computer science en_US
dc.subject Complex networks en_US
dc.title Robustness surfaces of complex networks en_US
dc.type Article (publisher version) en_US
dc.date.published 2014 en_US
dc.citation.doi 10.1038/srep06133 en_US
dc.citation.jtitle Scientific Reports en_US
dc.citation.spage article 6133 en_US
dc.citation.volume 4 en_US
dc.contributor.authoreid faryad en_US
dc.contributor.authoreid caterina en_US
dc.contributor.authoreid jlmarzol en_US


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