FedVANET: Efficient Federated Learning with Non-IID Data for Vehicular Ad Hoc Networks-Reference-Cited by-同舟云学术

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FedVANET: Efficient Federated Learning with Non-IID Data for Vehicular Ad Hoc Networks

Published:2021-12 Issue: Volume: Page:
ISSN:
Container-title:2021 IEEE Global Communications Conference (GLOBECOM)
language:
Short-container-title:

Author:

Li Beibei¹,Jiang Yukun¹,Sun Wenbin²,Niu Weina³,Wang Peiran¹

Affiliation:

1. School of Cyber Science and Engineering, Sichuan University,Chengdu,China,610065

2. School of Electronics and Information, Northwestern Polytechnical University,Xi'an,China,710129

3. School of Computer Science & Engineering, University of Electronic Science & Technology of China,China

Funder

China Postdoctoral Science Foundation

Fundamental Research Funds for the Central Universities

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9685019/9685006/09685068.pdf?arnumber=9685068

Reference12 articles.

1. A Survey on Federated Learning: The Journey From Centralized to Distributed On-Site Learning and Beyond

2. End to end learning for self-driving cars;bojarski;ArXiv Preprint,2016

3. Semi-Federated Learning

4. New Multi-Hop Clustering Algorithm for Vehicular Ad Hoc Networks

5. FedCluster: Boosting the Convergence of Federated Learning via Cluster-Cycling

Cited by 8 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. Contract Theory Based Incentive Mechanism for Clustered Vehicular Federated Learning;IEEE Transactions on Intelligent Transportation Systems;2024-07

2. Federated Learning for Vehicle Trajectory Prediction: Methodology and Benchmark Study;2024 International Joint Conference on Neural Networks (IJCNN);2024-06-30

3. Driving Towards Efficiency: Adaptive Resource-Aware Clustered Federated Learning in Vehicular Networks;2024 22nd Mediterranean Communication and Computer Networking Conference (MedComNet);2024-06-11

4. Adaptive federated reinforcement learning for critical realtime communications in UAV assisted vehicular networks;Computer Networks;2024-06

5. Federated Learning With Non-IID Data: A Survey;IEEE Internet of Things Journal;2024-06-01

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