Modelling and Analysis of 5G Networks Based on MEC-NFV for URLLC Services

Authors

Keywords:

URLLC, MEC, NFV, 5G Network, Queue Theory

Abstract

Ultra-Reliable and Low Latency Communications (URLLC) is a Fifth Generation (5G) or Beyond(B) 5G of Mobile Networks service that presents strict reliability and latency requirements. Multi-Access Edge Computing (MEC) and Network Function Virtualization (NFV) emerge as essential solutions since they allow network applications/functions to be virtualized and hosted closer to the end-user, improving reliability and latency. However, they may incur delay overheads (e.g., resource setup delay, failure events) to the dynamic resource provisioning that may impair the URLLC, which must be considered in the MECNFV node setting. This work addresses the resource provisioning for URLLC services in MEC-NFV-based networks, considering the Virtualized Network Function (VNF) setup time, failure occurrence and resource pre-initialization. A queue-based model is proposed to analyze the MEC-NFV node configuration in terms of average response time, blocking probability, and average number of active resources, under different service arrival and resource setup rates, maximum system capacity, number of resources and pre-initialized ones are carried out. The results show that the resource pre-initialization may mitigate the negative effect of the lower VNF setup rate.

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Author Biographies

Caio Souza, Federal University of Pernambuco

Caio Souza recebeu o t´ıtulo de Bacharel em Ciencia da Computac¸ao pela Universidade Federal Rural ˜
de Pernambuco (UFRPE) em 2020. Atualmente, e mestrando no Centro de Inform ´ atica (CIn) da ´Universidade Federal de Pernambuco (UFPE). Seus interesses de pesquisa incluem Wireless Network
Virtualization, 5G e B5G Networks e URLLC.

Marcos Falc˜ao, Federal University of Pernambuco

Marcos Falcao ˜ e graduado em Engenharia da ´Computac¸ao pela Universidade Federal de Pernambuco (UFPE), Brasil (2013). Ele recebeu o t´ıtulo de Mestre em Ciencia da Computac¸ ˆ ao em 2016 ˜pela mesma instituic¸ao e atualmente ˜ e doutorando ´tambem na UFPE. Seus interesses de pesquisa in- ´ cluem virtualizac¸ao de redes sem fio, redes de r ˜ adio ´ cognitivas, redes 5G e URLLC

Andson Balieiro, Federal University of Pernambuco

Andson Balieiro possui doutorado em Ciencia da ˆComputacao pela Universidade Federal de Pernambuco (UFPE). E professor do Centro de Informatica (CIn) da UFPE. Realiza pesquisas em Radio Cognitivo, URLLC, Virtualizac¸ao de Func ˜ oes de Rede, ˜Multiple Access Edge Computing (MEC) e Redes 5G e B5G/6G.

Kelvin Dias, Federal University of Pernambuco

Kelvin Dias concluiu o doutorado em Ciencia da ˆComputac¸ao pela Universidade Federal de Pernambuco (UFPE) em 2004. Foi professor adjunto da Universidade da Federal do Para de 2005 a 2010. ´Atualmente, e professor associado da UFPE desde ´2010. E bolsista de Produtividade do CNPQ (PQ- ´2). Realiza pesquisas sobre SDN, NFV, MEC, Fog Computing, Radios Cognitivos e Redes 5G/6G.

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Published

2021-04-12

How to Cite

Souza, C., Falc˜ao, M., Balieiro, A., & Dias, K. (2021). Modelling and Analysis of 5G Networks Based on MEC-NFV for URLLC Services. IEEE Latin America Transactions, 19(10), 1745–1753. Retrieved from https://latamt.ieeer9.org/index.php/transactions/article/view/5183

Issue

Vol. 19 No. 10 (2021): Issue with Special Section on 5G and B5G communications

Section

Special Section on 5G and B5G Communications

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