Addressing the 5G cell switch-off problem with a multi-objective cellular genetic algorithm
| dc.centro | E.T.S.I. Informática | en_US |
| dc.contributor.author | Luna, Francisco | |
| dc.contributor.author | Luque-Baena, Rafael Marcos | |
| dc.contributor.author | Martínez, Jesús | |
| dc.contributor.author | Padilla, Pablo | |
| dc.contributor.author | Valenzuela-Valdés, Juan Francisco | |
| dc.date.accessioned | 2018-07-16T11:17:17Z | |
| dc.date.available | 2018-07-16T11:17:17Z | |
| dc.date.created | 2018-07-09 | |
| dc.date.issued | 2018-07-16 | |
| dc.departamento | Lenguajes y Ciencias de la Computación | |
| dc.description | © 20xx IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. | en_US |
| dc.description.abstract | The power consumption foreseen for 5G networks is expected to be substantially greater than that of 4G systems, mainly because of the ultra-dense deployments required to meet the upcoming traffic demands. This paper deals with a multi- objective formulation of the Cell Switch-Off (CSO) problem, a well-known and effective approach to save energy in such dense scenarios, which is addressed with an accurate, yet rather unknown multi-objective metaheuristic called MOCell (multi- objective cellular genetic algorithm). It has been evaluated over a different set of networks of increasing densification levels. The results have shown that MOCell is able to reach major energy savings when compared to a widely used multi-objective algorithm. | en_US |
| dc.description.sponsorship | TIN2016-75097-P Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech. | en_US |
| dc.identifier.uri | https://hdl.handle.net/10630/16274 | |
| dc.language.iso | eng | en_US |
| dc.relation.eventdate | 9 de julio de 2018 | en_US |
| dc.relation.eventplace | Santa Clara, Estados Unidos | en_US |
| dc.relation.eventtitle | IEEE 5G World Forum | en_US |
| dc.rights | Attribution-NonCommercial-NoDerivatives 4.0 Internacional | * |
| dc.rights | Attribution-NoDerivatives 4.0 Internacional | * |
| dc.rights.accessRights | open access | en_US |
| dc.rights.uri | http://creativecommons.org/licenses/by-nd/4.0/ | * |
| dc.subject | Algoritmos genéticos - Congresos | en_US |
| dc.subject.other | Eficiencia energética | en_US |
| dc.subject.other | Apagado de celdas | en_US |
| dc.subject.other | 5G | en_US |
| dc.subject.other | Optimización multi-objetivo | en_US |
| dc.subject.other | Metaheurísticas | en_US |
| dc.subject.other | Algoritmo genético celular | en_US |
| dc.title | Addressing the 5G cell switch-off problem with a multi-objective cellular genetic algorithm | en_US |
| dc.type | conference output | en_US |
| dspace.entity.type | Publication | |
| relation.isAuthorOfPublication | 15881531-a431-477b-80d6-532058d8377c | |
| relation.isAuthorOfPublication.latestForDiscovery | 15881531-a431-477b-80d6-532058d8377c |
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