Edge Intelligence: Architectures, Challenges, and Applications

TL;DR

This paper provides a comprehensive survey of edge intelligence, covering its architecture, components, challenges, and applications, highlighting recent developments and future research directions in this rapidly growing field.

Contribution

It systematically classifies and analyzes the literature on edge intelligence, introducing a taxonomy of its four fundamental components and discussing open issues and solutions.

Findings

Identified four core components: caching, training, inference, offloading.

Provided a taxonomy categorizing solutions by problems, techniques, and goals.

Discussed open challenges and potential solutions in edge intelligence.

Abstract

Edge intelligence refers to a set of connected systems and devices for data collection, caching, processing, and analysis in locations close to where data is captured based on artificial intelligence. The aim of edge intelligence is to enhance the quality and speed of data processing and protect the privacy and security of the data. Although recently emerged, spanning the period from 2011 to now, this field of research has shown explosive growth over the past five years. In this paper, we present a thorough and comprehensive survey on the literature surrounding edge intelligence. We first identify four fundamental components of edge intelligence, namely edge caching, edge training, edge inference, and edge offloading, based on theoretical and practical results pertaining to proposed and deployed systems. We then aim for a systematic classification of the state of the solutions by examining research results and observations for each of the four components and present a taxonomy that includes practical problems, adopted techniques, and application goals. For each category, we elaborate, compare and analyse the literature from the perspectives of adopted techniques, objectives, performance, advantages and drawbacks, etc. This survey article provides a comprehensive introduction to edge intelligence and its application areas. In addition, we summarise the development of the emerging research field and the current state-of-the-art and discuss the important open issues and possible theoretical and technical solutions.