Modeling and Dimensioning of a Virtualized MME for 5G Mobile Networks
Metadatos
Mostrar el registro completo del ítemAutor
Prados Garzón, Jonathan; Ramos Muñoz, Juan José; Ameigeiras Gutiérrez, Pablo José; Andres-Maldonado, Pilar; López Soler, Juan ManuelEditorial
Institute of Electrical and Electronics Engineers (IEEE)
Materia
Evolved packet core fifth generation network functions virtualization scalability virtualization virtualized mobility management entity
Fecha
2017-05Referencia bibliográfica
J. Prados-Garzon, J. J. Ramos-Munoz, P. Ameigeiras, P. Andres-Maldonado and J. M. Lopez-Soler, "Modeling and Dimensioning of a Virtualized MME for 5G Mobile Networks," in IEEE Transactions on Vehicular Technology, vol. 66, no. 5, pp. 4383-4395, May 2017, doi: 10.1109/TVT.2016.2608942.
Patrocinador
This work was supported in part by the Spanish Ministry of Economy and Competitiveness and the European Regional Development Fund (project TIN2013-46223-P) and in part by the Spanish Ministry of Education, Culture, and Sport under FPU Grant 13/04833.Resumen
Network function virtualization is considered one of
the key technologies for developing future mobile networks. In this
paper, we propose a theoretical framework to evaluate the performance of a Long-Term Evolution (LTE) virtualized mobility management entity (vMME) hosted in a data center. This theoretical
framework consists of 1) a queuing network to model the vMME
in a data center and 2) analytic expressions to estimate the overall
mean system delay and the signaling workload to be processed by
the vMME. We validate our mathematical model by simulation.
One direct use of the proposed model is vMME dimensioning, i.e.,
to compute the number of vMME processing instances to provide
a target system delay given the number of users in the system.
Additionally, the paper includes a scalability analysis of the system. In our study, we consider the billing model and a data center
setup of Amazon Elastic Compute Cloud service and estimate the
processing time of MME processing instances for different LTE
control procedures experimentally. For the considered setup, our
results show that the vMME is scalable for signaling workloads
up to 37 000 LTE control procedures per second for a target mean
system delay of 1 ms. The system design and database performance
assumed imposes this limit in the system scalability.