A survey of multi-access edge computing in 5G and beyond : fundamentals, technology integration, and state-of-the-art

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

Introduction to the Computation Offloading from Mobile Devices to the Edge of Mobile Network

This paper introduces the concept of Small Cell Cloud (SCC) composed of multiple Cloud-enabled Small Cells (CeSCs), which provide radio connection for mobile User Equipment (UE) such as smart-phones or wearables such as smart glasses. Moreover, CeSCs host computations offloaded from UEs in a way similar to centralized cloud, yet different in its proximity to users. Proposed client-server architecture of SCC con-veys mechanisms for moving offloaded computations from the UEs to CeSCs. Real-life implementation of the SCC architecture relies on custom-developed Of-floading Framework which is responsible for low-level communication between the UE and the SCC. The Of-floading Framework is accompanied by an Augmented Reality (AR) app, which employs intensive computa-tions for discovery of places of interest. Such app is latency-sensitive, a criterion which makes computation offloading beneficial due to its ability to decrease la-tency. The combination of the O˜oading Framework and the AR app makes up an SCC testbed used for fur-ther performance evaluation. Numerous measurements are carried out to examine the impact of various pa-rameters. Based on Proof-of-concept implementation and thorough measurements, it has been revealed that computation offloading can decrease overall latency as much as to 47 % and energy consumption on the UE side to 56