A Survey of Multi-Access Edge Computing in 5G and Beyond: Fundamentals, Technology Integration, and State-of-the-Art

Abstract

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.

Artificial Intelligence (AI) and Big Data for Coronavirus (COVID-19) Pandemic: A Survey on the State-of-the-Arts

“…These works are advantageous since smart devices are daily used for multi-purposes. Moreover, the emergence of cloud and edge computing can effectively overcome the limitation of batter, storage, and computing capabilities [33], [34].…”

“…Wireless connectivity, e.g., WiFi, 4G, and 5G, has been widely deployed in almost all the countries, so every individual with a mobile phone can connect to the Internet and can do many activities online [121]. The DL model can be trained in the cloud, even at a server collocated at the network edge, which is then pushed to mobile phone for further purpose [33]. For example, by using the embedded cameras and biosensors, a mobile phone can collect personal information, for example, X-ray and CT images, cough sound, and heart rate, which may be encrypted and compressed before sending to the cloud for training [31], [56].…”

A New Green Prospective of Non-orthogonal Multiple Access (NOMA) for 5G

“…Energy efficiency for NOMA using edge computing has been sought in [153,154]. Mobile edge computing incorporated with NOMA can serve multiple users using the same bandwidth and time [155]. Further, the computing done at the edge of the network results in a significant reduction in network traffic and resource utilization and an enhancement in energy efficiency.…”

Multi-Access Edge Computing Empowered Heterogeneous Networks: A Novel Architecture and Potential Works

“…In general, MEC use cases can be categorized into consumer-oriented services, operator and third-party services, and network performance and quality-of-experience (QoE) improvements [6,28,29]. Among them, computation offloading is regarded as the main use case for consumer-oriented services so that it enables end devices to run new resource-demanding applications, prolong the battery lives, and reduce the end-to-end latency.…”