Improving the Energy Efficiency of Software-Defined Networks through the Prediction of Network Configurations

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AudienciaPúblico en generales_ES
CoberturaMéxicoes_ES
Fecha de ingreso2026-09-15T00:31:53Z
Fecha de publicación2022-01-01
ResumenDuring the last years, huge efforts have been conducted to reduce the Information and Communication Technology (ICT) sector energy consumption due to its impact on the carbon footprint, in particular, the one coming from networking equipment. Although the irruption of programmable and softwarized networks has opened new perspectives to improve the energy-efficient solutions already defined for traditional IP networks, the centralized control of the Software-Defined Networking (SDN) paradigm entails an increase in the time required to compute a change in the network configuration and the corresponding actions to be carried out (e.g., installing/removing rules, putting links to sleep, etc.). In this paper, a Machine Learning solution based on Logistic Regression is proposed to predict energy-efficient network configurations in SDN. This solution does not require executing optimal or heuristic solutions at the SDN controller, which otherwise would result in higher computation times. Experimental results over a realistic network topology show that our solution is able to predict network configurations with a high feasibility (>95%), hence improving the energy savings achieved by a benchmark heuristic based on Genetic Algorithms. Moreover, the time required for computation is reduced by a factor of more than 500,000 times.es_ES
Doihttps://doi.org/10.3390/electronics11172739es_ES
URIhttps://riuat.uat.edu.mx/handle/123456789/3631
Idiomaenes_ES
EditorialMDPI AGes_ES
RelaciónElectronicses_ES
URL relacionadohttps://doi.org/10.3390/electronics11172739es_ES
DerechosAcceso restringido / Suscripción (Metadatos de producción científica)es_ES
Licenciahttp://purl.org/coar/access_right/c_16eces_ES
FuenteElectronics
TítuloImproving the Energy Efficiency of Software-Defined Networks through the Prediction of Network Configurationses_ES
TipoArtículoes_ES
ArbitradoHa sido Arbitradoes_ES
AutorJiménez-Lázaro, Manuel
AutorHerrera, Juan Luis
AutorBerrocal, Javier
AutorGalán-Jiménez, Jaime
AutorJiménez-Lázaro, Manueles_ES
AutorHerrera, Juan Luises_ES
AutorBerrocal, Javieres_ES
AutorGalán-Jiménez, Jaimees_ES
InstituciónUniversidad Autónoma de Tamaulipas
InstituciónUniversidad Autónoma de Tamaulipases_ES
Número17es_ES
Rango de páginas2739es_ES
URL relacionadahttps://doi.org/10.3390/electronics11172739
Tipo de artículoIndexado
Tipo de artículoIndexadoes_ES
Volumen11es_ES

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