Deep Reinforcement Learning-Based Resource Management for Flexible Mobile Edge Computing: Architectures, Applications, and Research Issues

Kezhi Wang, Liang Wang, Cunhua Pan, Hong Ren

Research output: Contribution to journalArticlepeer-review

Abstract

In this article, we introduce autonomous vehicleassisted mobile edge computing (AV-MEC), including unmanned ground vehicle (UGV)- and unmanned aerial vehicle (UAV)-assisted MEC, where the UAV/UGV can be deployed and carry the computing server to serve ground mobile devices (MDs). We first discuss applications and main research problems. Then, deep reinforcement learning (DRL)-based solutions are introduced, explored, and demonstrated. We also discuss challenges and future research directions for an AV-MEC system with DRL being applied to it.
Original languageEnglish
Number of pages9
JournalIEEE Vehicular Technology Magazine
Early online date20 Apr 2022
DOIs
Publication statusE-pub ahead of print - 20 Apr 2022

Fingerprint

Dive into the research topics of 'Deep Reinforcement Learning-Based Resource Management for Flexible Mobile Edge Computing: Architectures, Applications, and Research Issues'. Together they form a unique fingerprint.

Cite this