Actions at the Edge: Jointly Optimizing the Resources in Multi-access Edge Computing

TL;DR

This paper explores the challenges and solutions in optimizing resource allocation in multi-access edge computing (MEC) to enhance real-time processing, edge intelligence, and user experience for cyber-physical systems.

Contribution

It provides a comprehensive overview of MEC concepts, architectures, modeling approaches, and future research directions, serving as an introductory guide for new researchers.

Findings

Analysis of MEC performance metrics

Identification of key applications and architectural designs

Discussion of modeling approaches and future research challenges

Abstract

Multi-access edge computing (MEC) is an emerging paradigm that pushes resources for sensing, communications, computing, storage and intelligence (SCCSI) to the premises closer to the end users, i.e., the edge, so that they could leverage the nearby rich resources to improve their quality of experience (QoE). Due to the growing emerging applications targeting at intelligentizing life-sustaining cyber-physical systems, this paradigm has become a hot research topic, particularly when MEC is utilized to provide edge intelligence and real-time processing and control. This article is to elaborate the research issues along this line, including basic concepts and performance metrics, killer applications, architectural design, modeling approaches and solutions, and future research directions. It is hoped that this article provides a quick introduction to this fruitful research area particularly for beginning researchers.