A Deep Reinforcement Learning-Based Offloading Scheme for Multi-Access Edge Computing-Supported eXtended Reality Systems-Reference-Cited by-同舟云学术

A Deep Reinforcement Learning-Based Offloading Scheme for Multi-Access Edge Computing-Supported eXtended Reality Systems

Published:2023-01 Issue:1 Volume:72 Page:1254-1264
ISSN:0018-9545
Container-title:IEEE Transactions on Vehicular Technology
language:
Short-container-title:IEEE Trans. Veh. Technol.

Author:

Trinh Bao¹^ORCID,Muntean Gabriel-Miro¹^ORCID

Affiliation:

1. Insight SFI Research Centre for Data Analytics and Performance Engineering Laboratory, School of Electronic Engineering, Dublin City University, 9 Dublin, Ireland

Funder

Science Foundation Ireland

Insight SFI Research Centre for Data Analytics

European Regional Development Fund

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Computer Networks and Communications,Aerospace Engineering,Automotive Engineering

Link

http://xplorestaging.ieee.org/ielx7/25/10017140/09894514.pdf?arnumber=9894514

Reference48 articles.

1. Energy-efficient dynamic offloading and resource scheduling in mobile cloud computing

2. Computation Offloading and Resource Allocation in Wireless Cellular Networks With Mobile Edge Computing

3. Learning-Based Computation Offloading for IoT Devices With Energy Harvesting

4. Deep Reinforcement Learning for Intelligent Internet of Vehicles: An Energy-Efficient Computational Offloading Scheme

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