Efficient End–Edge–Cloud Task Offloading in 6G Networks Based on Multiagent Deep Reinforcement Learning-Reference-Cited by-同舟云学术

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Efficient End–Edge–Cloud Task Offloading in 6G Networks Based on Multiagent Deep Reinforcement Learning

Published:2024-06-01 Issue:11 Volume:11 Page:20260-20270
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

She Hao¹^ORCID,Yan Lixing¹,Guo Yongan¹^ORCID

Affiliation:

1. College of Telecommunications and Information Engineering, the Engineering Research Center of Health Service System Based on Ubiquitous Wireless Networks, Ministry of Education, Edge Intelligence Research Institute, Nanjing University of Posts and Telecommunications, Nanjing, Jiangsu, China

Funder

Frontier Leading Technology Basic Research Project of Jiangsu Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/6488907/10536937/10477307.pdf?arnumber=10477307

Reference45 articles.

1. Learning-Based Task Offloading for Mobile Edge Computing

2. Mobility-Aware Computation Offloading in Edge Computing using Machine Learning

3. Latency Optimization for Resource Allocation in Mobile-Edge Computation Offloading

4. The Roadmap to 6G: AI Empowered Wireless Networks

5. A Functional Architecture for 6G Special-Purpose Industrial IoT Networks

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