RT info:eu-repo/semantics/article
T1 A Genetic Algorithm for VNF Provisioning in NFV-Enabled Cloud/MEC RAN Architectures
A1 Ruiz Pérez, Lidia
A1 Durán Barroso, Ramón José
A1 Miguel Jiménez, Ignacio de
A1 Khodashenas, Pouria S.
A1 Pedreno Manresa, José Juan
A1 Merayo Álvarez, Noemí
A1 Aguado Manzano, Juan Carlos
A1 Pavón Marino, Pablo
A1 Siddiqui, Shuaib
A1 Mata, Javier
A1 Fernández Reguero, Patricia
A1 Lorenzo Toledo, Rubén Mateo
A1 Abril Domingo, Evaristo José
K1 Redes ópticas
K1 Optical networks
AB 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.
PB MDPI
SN 2076-3417
YR 2018
FD 2018
LK http://uvadoc.uva.es/handle/10324/33560
UL http://uvadoc.uva.es/handle/10324/33560
LA eng
NO Applied Sciences, 2018, vol. 8, n. 12, 2614
NO Producción Científica
DS UVaDOC
RD 24-nov-2024