Modeling and Dimensioning of a Virtualized MME for 5G Mobile Networks
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AuthorPrados-Garzon, Jonathan; Ramos Muñoz, Juan José; Ameigeiras Gutiérrez, Pablo José; Andres-Maldonado, Pilar; López Soler, Juan Manuel
Institute of Electrical and Electronics Engineers (IEEE)
Evolved packet corefifth generationnetwork functions virtualizationscalabilityvirtualizationvirtualized mobility management entity
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.
SponsorshipThis 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.
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.