Market Analysis of MEC-Assisted Beyond 5G Ecosystem

• Published in: IEEE access Vol. 9; pp. 53996 - 54008
• Main Authors: Nakazato, Jin, Nakamura, Makoto, Yu, Tao, Li, Zongdian, Maruta, Kazuki, Tran, Gia Khanh, Sakaguchi, Kei
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.01.2021; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: 5G and beyond; 5G mobile communication; CAPEX; Cellular communication; Cellular networks; Cloud computing; cloud owner; cloud ownercess edge computing; Computational modeling; ecosystem; Ecosystems; Edge computing; Game theory; heterogeneous cellular networks; Mobile computing; Mobile edge computing; Model testing; multi-access edge computing; OPEX; Optimization; Revenue; telecom operator; Telecommunications; Telecommunications industry; Traffic management; Wireless networks
• ISSN: 2169-3536; 2169-3536
• DOI: 10.1109/ACCESS.2021.3068839

The quality-of-service (QoS)/quality-of-experience (QoE) demands of mobile services are soaring and have overwhelmed the obsolescent capability of 3G and 4G cellular networks. The emerging 5G networks will bring an unprecedented promotion in transmission data rates. However, the satisfaction of some service requirements is still in dilemma, especially the end-to-end (E2E) latency which varies in different applications. Multi-access edge computing (MEC), a promising technology in 5G cellular networks, can provide ultra-low E2E latency and reduce traffic load on mobile backhaul networks. The potential benefits of MEC for 5G and beyond services have been explored by preliminary studies. What remains is the uncertainty of revenue from the investment of MEC which will shake operators' decisions about whether and how to deploy MEC in cellular networks. In this light, this paper designs a MEC-assisted 5G and beyond ecosystem inclusive of three players: private (local) telecom operators, backhaul, and cloud service owners. We propose a revenue maximization model for private (local) telecom operators and cloud service owners to minimize the cost from the end-user perspective while satisfying the latency requirement. The derived model indicates that two players' revenues can be maximized by optimizing MEC resources and backhaul capacity. The game-theoretic analyses also reveal the optimized hybrid strategy of MEC and cloud for efficient mobile traffic management.