A Federated Learning-Based Edge Caching Approach for Mobile Edge Computing-Enabled Intelligent Connected Vehicles
Author:
Affiliation:
1. School of Computer and Artificial Intelligence, Wuhan University of Technology, Wuhan, China
2. School of Management, Wuhan University of Technology, Wuhan, China
Funder
National Natural Science Foundation of China
Science and Technology on Information Systems Engineering Laboratory of National University of Defense Technology
Key Laboratory of Southeast Coast Marine Information Intelligent Perception and Application of Ministry of Natural Resources
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Subject
Computer Science Applications,Mechanical Engineering,Automotive Engineering
Link
http://xplorestaging.ieee.org/ielx7/6979/10057093/09966317.pdf?arnumber=9966317
Reference27 articles.
1. Low-latency edge cooperation caching based on base station cooperation in SDN based MEC
2. Intermediate data placement and cache replacement strategy under Spark platform
3. Mobility-Aware Proactive Edge Caching for Connected Vehicles Using Federated Learning
4. Federated Learning Based Proactive Content Caching in Edge Computing
5. Deep Reinforcement Learning-Based Edge Caching in Wireless Networks
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