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Título: A Genetic Algorithm for VNF Provisioning in NFV-Enabled Cloud/MEC RAN Architectures
Autor: Ruiz, Lidia
Durán Barroso, Ramón José
De Miguel, Ignacio
Khodashenas, Pouria S.
Pedreno Manresa, José Juan
Merayo, Noemí
Aguado, Juan Carlos
Pavón Marino, Pablo
Siddiqui, Shuaib
Mata, Javier
Fernández, Patricia
Lorenzo, Rubén Mateo
Abril Domingo, Evaristo José
Año del Documento: 2018
Editorial: MDPI
Descripción: Producción Científica
Documento Fuente: Applied Sciences, 2018, 8 (12), 2614
Resumen: 5G technologies promise to bring new network and service capacities and are expected to introduce significant architectural and service deployment transformations. The Cloud-Radio Access Networks (C-RAN) architecture, enabled by the combination of Software Defined Networking (SDN), Network Function Virtualization (NFV) and Mobile Edge Computing (MEC) technologies, play a key role in the development of 5G. In this context, this paper addresses the problems of Virtual Network Functions (VNF) provisioning (VNF-placement and service chain allocation) in a 5G network. In order to solve that problem, we propose a genetic algorithm that, considering both computing resources and optical network capacity, minimizes both the service blocking rate and CPU usage. In addition, we present an algorithm extension that adds a learning stage and evaluate the algorithm performance benefits in those scenarios where VNF allocations can be reconfigured. Results reveal and quantify the advantages of reconfiguring the VNF mapping depending on the current demands. Our methods outperform previous proposals in the literature, reducing the service blocking ratio while saving energy by reducing the number of active core CPUs.
Palabras Clave: Red óptica
Optical networks
ISSN: 2076-3417
Revisión por Pares: SI
DOI: https://doi.org/10.3390/app8122614
Patrocinador: Ministerio de Economía, Industria y Competitividad (Project TEC2014-53071-C3-2-P, TEC2017-84423-C3-1-P, TEC2015-71932-REDT),
Ministerio de Educación, Cultura y Deporte (Proyect BES-2015-074514 and FPU14/04227)
European H2020-ICT-2016-2 METRO-HAUL (no. 761727)
info:eu-repo/grantAgreement/EC/H2020/761727
Version del Editor: https://www.mdpi.com/2076-3417/8/12/2614
Idioma: eng
URI: http://uvadoc.uva.es/handle/10324/33560
Derechos: info:eu-repo/semantics/openAccess
Aparece en las colecciones:Documentos OpenAire(Open Access Infrastructure for Research in Europe)
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