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Calculation of the Connected Dominating Set Considering Vertex Importance Metrics
The computation of a set constituted by few vertices to define a virtual backbone supporting information interchange is a problem that arises in many areas when analysing networks of different natures, like wireless, brain, or social networks. Recent papers propose obtaining such a set of vertices b...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2018
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512650/ https://www.ncbi.nlm.nih.gov/pubmed/33265178 http://dx.doi.org/10.3390/e20020087 |
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author | Vazquez-Araujo, Francisco Dapena, Adriana Souto-Salorio, María José Castro, Paula M. |
author_facet | Vazquez-Araujo, Francisco Dapena, Adriana Souto-Salorio, María José Castro, Paula M. |
author_sort | Vazquez-Araujo, Francisco |
collection | PubMed |
description | The computation of a set constituted by few vertices to define a virtual backbone supporting information interchange is a problem that arises in many areas when analysing networks of different natures, like wireless, brain, or social networks. Recent papers propose obtaining such a set of vertices by computing the connected dominating set (CDS) of a graph. In recent works, the CDS has been obtained by considering that all vertices exhibit similar characteristics. However, that assumption is not valid for complex networks in which their vertices can play different roles. Therefore, we propose finding the CDS by taking into account several metrics which measure the importance of each network vertex e.g., error probability, entropy, or entropy variation (EV). |
format | Online Article Text |
id | pubmed-7512650 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-75126502020-11-09 Calculation of the Connected Dominating Set Considering Vertex Importance Metrics Vazquez-Araujo, Francisco Dapena, Adriana Souto-Salorio, María José Castro, Paula M. Entropy (Basel) Article The computation of a set constituted by few vertices to define a virtual backbone supporting information interchange is a problem that arises in many areas when analysing networks of different natures, like wireless, brain, or social networks. Recent papers propose obtaining such a set of vertices by computing the connected dominating set (CDS) of a graph. In recent works, the CDS has been obtained by considering that all vertices exhibit similar characteristics. However, that assumption is not valid for complex networks in which their vertices can play different roles. Therefore, we propose finding the CDS by taking into account several metrics which measure the importance of each network vertex e.g., error probability, entropy, or entropy variation (EV). MDPI 2018-01-28 /pmc/articles/PMC7512650/ /pubmed/33265178 http://dx.doi.org/10.3390/e20020087 Text en © 2018 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 Vazquez-Araujo, Francisco Dapena, Adriana Souto-Salorio, María José Castro, Paula M. Calculation of the Connected Dominating Set Considering Vertex Importance Metrics |
title | Calculation of the Connected Dominating Set Considering Vertex Importance Metrics |
title_full | Calculation of the Connected Dominating Set Considering Vertex Importance Metrics |
title_fullStr | Calculation of the Connected Dominating Set Considering Vertex Importance Metrics |
title_full_unstemmed | Calculation of the Connected Dominating Set Considering Vertex Importance Metrics |
title_short | Calculation of the Connected Dominating Set Considering Vertex Importance Metrics |
title_sort | calculation of the connected dominating set considering vertex importance metrics |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7512650/ https://www.ncbi.nlm.nih.gov/pubmed/33265178 http://dx.doi.org/10.3390/e20020087 |
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