TY - JOUR
T1 - A Survey of Multi-Access Edge Computing in 5G and Beyond
T2 - Fundamentals, Technology Integration, and State-of-the-Art
AU - Pham, Quoc Viet
AU - Fang, Fang
AU - Ha, Vu Nguyen
AU - Piran, Md Jalil
AU - Le, Mai
AU - Le, Long Bao
AU - Hwang, Won Joo
AU - Ding, Zhiguo
N1 - Funding Information:
This work was supported by the National Research Foundation of Korea (NRF) funded by the Korea Government (MSIT) under Grant NRF-2019R1C1C1006143 and Grant NRF-2019R1I1A3A01060518. This work was also supported by Institute of Information & communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (No. 2020-0-01450, Artificial Intelligence Convergence Research Center [Pusan National University]).
Publisher Copyright:
© 2013 IEEE.
PY - 2020
Y1 - 2020
N2 - Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud-computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research.
AB - Driven by the emergence of new compute-intensive applications and the vision of the Internet of Things (IoT), it is foreseen that the emerging 5G network will face an unprecedented increase in traffic volume and computation demands. However, end users mostly have limited storage capacities and finite processing capabilities, thus how to run compute-intensive applications on resource-constrained users has recently become a natural concern. Mobile edge computing (MEC), a key technology in the emerging fifth generation (5G) network, can optimize mobile resources by hosting compute-intensive applications, process large data before sending to the cloud, provide the cloud-computing capabilities within the radio access network (RAN) in close proximity to mobile users, and offer context-aware services with the help of RAN information. Therefore, MEC enables a wide variety of applications, where the real-time response is strictly required, e.g., driverless vehicles, augmented reality, robotics, and immerse media. Indeed, the paradigm shift from 4G to 5G could become a reality with the advent of new technological concepts. The successful realization of MEC in the 5G network is still in its infancy and demands for constant efforts from both academic and industry communities. In this survey, we first provide a holistic overview of MEC technology and its potential use cases and applications. Then, we outline up-to-date researches on the integration of MEC with the new technologies that will be deployed in 5G and beyond. We also summarize testbeds and experimental evaluations, and open source activities, for edge computing. We further summarize lessons learned from state-of-the-art research works as well as discuss challenges and potential future directions for MEC research.
KW - 5G and beyond network
KW - edge computing
KW - heterogeneous networks
KW - Internet of Things
KW - machine learning
KW - non-orthogonal multiple access
KW - testbeds
KW - unmanned aerial vehicle
KW - wireless power transfer and energy harvesting
UR - http://www.scopus.com/inward/record.url?scp=85087817962&partnerID=8YFLogxK
U2 - 10.1109/ACCESS.2020.3001277
DO - 10.1109/ACCESS.2020.3001277
M3 - Review article
AN - SCOPUS:85087817962
SN - 2169-3536
VL - 8
SP - 116974
EP - 117017
JO - IEEE Access
JF - IEEE Access
M1 - 9113305
ER -