CASIA OpenIR
Beyond the Edge: An Advanced Exploration of Reinforcement Learning for Mobile Edge Computing, its Applications, and Future Research Trajectories
Yang,Ning; Chen,Shuo; Zhang,Haijun; Berry,Randall
Source PublicationIEEE Communications Surveys and Tutorials
2024
Pages50
Abstract

Mobile Edge Computing (MEC) broadens the scope of computation and storage beyond the central network, incorporating edge nodes close to end devices. This expansion facilitates the implementation of large-scale "connected things" within edge networks. The advent of applications necessitating real-time, high-quality service presents several challenges, such as low latency, high data rate, reliability, efficiency, and security, all of which demand resolution. The incorporation of reinforcement learning (RL) methodologies within MEC networks promotes a deeper understanding of mobile user behaviors and network dynamics, thereby optimizing resource use in computing and communication processes. This paper offers an exhaustive survey of RL applications in MEC networks, initially presenting an overview of RL from its fundamental principles to the latest advanced frameworks. Furthermore, it outlines various RL strategies employed in offloading, caching, and communication within MEC networks. Finally, it explores open issues linked with software and hardware platforms, representation, RL robustness, safe RL, large-scale scheduling, generalization, security, and privacy. The paper proposes specific RL techniques to mitigate these issues and provides insights into their practical applications.

KeywordReinforcement learning, mobile edge computing, offloading scheduling, content caching, and communication
IS Representative Paper
Sub direction classification决策智能理论与方法
planning direction of the national heavy laboratory其他
Paper associated data
Document Type期刊论文
Identifierhttp://ir.ia.ac.cn/handle/173211/57100
Collection中国科学院自动化研究所
Recommended Citation
GB/T 7714
Yang,Ning,Chen,Shuo,Zhang,Haijun,et al. Beyond the Edge: An Advanced Exploration of Reinforcement Learning for Mobile Edge Computing, its Applications, and Future Research Trajectories[J]. IEEE Communications Surveys and Tutorials,2024:50.
APA Yang,Ning,Chen,Shuo,Zhang,Haijun,&Berry,Randall.(2024).Beyond the Edge: An Advanced Exploration of Reinforcement Learning for Mobile Edge Computing, its Applications, and Future Research Trajectories.IEEE Communications Surveys and Tutorials,50.
MLA Yang,Ning,et al."Beyond the Edge: An Advanced Exploration of Reinforcement Learning for Mobile Edge Computing, its Applications, and Future Research Trajectories".IEEE Communications Surveys and Tutorials (2024):50.
Files in This Item: Download All
File Name/Size DocType Version Access License
Beyond_the_Edge_An_A(1694KB)期刊论文作者接受稿开放获取CC BY-NC-SAView Download
Related Services
Recommend this item
Bookmark
Usage statistics
Export to Endnote
Google Scholar
Similar articles in Google Scholar
[Yang,Ning]'s Articles
[Chen,Shuo]'s Articles
[Zhang,Haijun]'s Articles
Baidu academic
Similar articles in Baidu academic
[Yang,Ning]'s Articles
[Chen,Shuo]'s Articles
[Zhang,Haijun]'s Articles
Bing Scholar
Similar articles in Bing Scholar
[Yang,Ning]'s Articles
[Chen,Shuo]'s Articles
[Zhang,Haijun]'s Articles
Terms of Use
No data!
Social Bookmark/Share
File name: Beyond_the_Edge_An_Advanced_Exploration_of_Reinforcement_Learning_for_Mobile_Edge_Computing_its_Applications_and_Future_Research_Trajectories.pdf
Format: Adobe PDF
All comments (0)
No comment.
 

Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.