Federated Learning for Computational Offloading and Resource Management of Vehicular Edge Computing in 6G-V2X Network-Reference-Cited by-同舟云学术

Federated Learning for Computational Offloading and Resource Management of Vehicular Edge Computing in 6G-V2X Network

Published:2024-02 Issue:1 Volume:70 Page:3827-3847
ISSN:0098-3063
Container-title:IEEE Transactions on Consumer Electronics
language:
Short-container-title:IEEE Trans. Consumer Electron.

Author:

Hasan Mohammad Kamrul¹^ORCID,Jahan Nusrat¹,Nazri Mohd Zakree Ahmad¹,Islam Shayla²^ORCID,Attique Khan Muhammad³^ORCID,Alzahrani Ahmed Ibrahim⁴^ORCID,Alalwan Nasser⁴^ORCID,Nam Yunyoung⁵^ORCID

Affiliation:

1. Center for Cyber Security, Faculty of Information Science and Technology, Universiti Kebangsaan Malaysia, Bangi, Malaysia

2. Institute of Computer Science and Digital Innovation, UCSI University, Kuala Lumpur, Malaysia

3. Department of Computer Science, HITEC University, Taxila, Pakistan

4. Computer Science Department, Community College, King Saud University, Riyadh, Saudi Arabia

5. Department of Computer Science and Engineering, ICT Convergence Research Center, Soonchunhyang University, Asan, South Korea

Funder

Researchers Supporting Project

King Saud University, Riyadh, Saudi Arabia

National Research Foundation of Kore

Korea Government

Soonchunhyang University Research Fund

Universiti Kebangsaan Malysia Under Research

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx7/30/10510045/10415079.pdf?arnumber=10415079

Reference104 articles.

1. 6G for Vehicle-to-Everything (V2X) Communications: Enabling Technologies, Challenges, and Opportunities

2. VECFrame: A Vehicular Edge Computing Framework for Connected Autonomous Vehicles

3. Edge Intelligence in Intelligent Transportation Systems: A Survey

4. Emerging Technologies for V2X Communication and Vehicular Edge Computing in the 6G era: Challenges and Opportunities for Sustainable IoV

5. 6G Wireless Systems: Vision, Requirements, Challenges, Insights, and Opportunities

Cited by 10 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. A joint optimization of resource allocation management and multi-task offloading in high-mobility vehicular multi-access edge computing networks;Ad Hoc Networks;2025-01

2. A Survey on Artificial-Intelligence-Based Internet of Vehicles Utilizing Unmanned Aerial Vehicles;Drones;2024-07-29

3. Ensuring Privacy and Communication Efficiency Through Partial Parameter Exchange in Collaborative Learning for Vehicular Applications;2024 IEEE International Black Sea Conference on Communications and Networking (BlackSeaCom);2024-06-24

4. A Survey of Machine Learning in Edge Computing: Techniques, Frameworks, Applications, Issues, and Research Directions;Technologies;2024-06-03

5. Federated learning enables 6 G communication technology: Requirements, applications, and integrated with intelligence framework;Alexandria Engineering Journal;2024-03