TY - GEN
T1 - Design of MEC 5G cellular networks
T2 - 2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020
AU - Nakazato, Jin
AU - Nakamura, Makoto
AU - Yu, Tao
AU - Li, Zongdian
AU - Tran, Gia Khanh
AU - Sakaguchi, Kei
N1 - Publisher Copyright:
© 2020 IEEE.
PY - 2020/6
Y1 - 2020/6
N2 - Recently, the mobile traffic demand is increasing due to the drastic growth in the number of connected devices and smart services utilizing wireless cellular networks. In order to deal with this tough challenge, a key technology in 5G cellular networks, Multi-Access Edge Computing (MEC) which can provide ultra-low end-to-end latency, significant reduction of traffic load on backhaul, etc., has come into sight. The potential benefits of MEC in 5G and beyond have been revealed by plenty of state-of-the-art works. However, it leaves a difficult problem for the operators, which is to determine whether and how to deploy MEC in cellular networks due to the uncertainty of feedback from the investment on MEC. Although, there were a few works studying on the optimization of the number of MEC from the viewpoint of telecom operators, their contribution focus only on telecom operators rather than taking other operators (backhaul owners, Cloud owners, etc.) into account. In this paper, we propose a social maximization revenue model with the investment strategy for the telecom operators who decide the number of MEC and the backhaul owner who lease the backhaul capacity. The numerical results indicate that the optimal number of MEC and backhaul capacity that maximize the two players' profit is the same. Hence, it turns out that the advantage of MEC can be highlighted by using both Cloud and edge resource in parallel rather than processing all traffic on the MEC side.
AB - Recently, the mobile traffic demand is increasing due to the drastic growth in the number of connected devices and smart services utilizing wireless cellular networks. In order to deal with this tough challenge, a key technology in 5G cellular networks, Multi-Access Edge Computing (MEC) which can provide ultra-low end-to-end latency, significant reduction of traffic load on backhaul, etc., has come into sight. The potential benefits of MEC in 5G and beyond have been revealed by plenty of state-of-the-art works. However, it leaves a difficult problem for the operators, which is to determine whether and how to deploy MEC in cellular networks due to the uncertainty of feedback from the investment on MEC. Although, there were a few works studying on the optimization of the number of MEC from the viewpoint of telecom operators, their contribution focus only on telecom operators rather than taking other operators (backhaul owners, Cloud owners, etc.) into account. In this paper, we propose a social maximization revenue model with the investment strategy for the telecom operators who decide the number of MEC and the backhaul owner who lease the backhaul capacity. The numerical results indicate that the optimal number of MEC and backhaul capacity that maximize the two players' profit is the same. Hence, it turns out that the advantage of MEC can be highlighted by using both Cloud and edge resource in parallel rather than processing all traffic on the MEC side.
KW - Backhaul Owner
KW - Business Model
KW - Heterogeneous Networks
KW - Multi-Access Edge Computing
KW - Revenue
KW - Telecom Operator
UR - https://www.scopus.com/pages/publications/85090289705
U2 - 10.1109/ICCWorkshops49005.2020.9145269
DO - 10.1109/ICCWorkshops49005.2020.9145269
M3 - Conference contribution
AN - SCOPUS:85090289705
T3 - 2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020 - Proceedings
BT - 2020 IEEE International Conference on Communications Workshops, ICC Workshops 2020 - Proceedings
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 7 June 2020 through 11 June 2020
ER -