| Paper Abstract and Keywords |
| Presentation |
2025-11-06 14:55
Intelligent Training Control for Hierarchical Federated Learning in Dynamic Vehicular Environments
Zhaoyang Du, Celimuge Wu, Yangfei Lin, Jiale Wu (UEC) |
| Abstract |
(in Japanese) |
(See Japanese page) |
| (in English) |
Federated Learning (FL) has emerged as a promising solution for enabling privacy-preserving distributed model training in vehicular networks. However, the highly dynamic environment of the Internet of Vehicles (IoV) and communication constraints often result in inefficient training convergence and degraded global model performance. In this paper, we propose a Deep Q-Network (DQN)-based adaptive local training strategy tailored for hierarchical federated learning (HFL) in IoV. By formulating the training control process as a Markov Decision Process (MDP), each vehicle client dynamically determines the number of local training epochs according to real-time training feedback and network conditions. The proposed strategy is integrated into a three-tier HFL framework involving vehicles, roadside units (RSUs), and a cloud server. Extensive experiments demonstrate that our method improves final model accuracy and reduces total training time compared to existing baselines. The results confirm that adaptive control could effectively balance communication cost and model convergence in HFL systems under realistic vehicular conditions. |
| Keyword |
(in Japanese) |
(See Japanese page) |
| (in English) |
Federated Learning / Internet of Vehicles / Deep Reinforcement Learning / DQN / / / / |
| Reference Info. |
ITE Tech. Rep. |
| Paper # |
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| Date of Issue |
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| ISSN |
Online edition: ISSN 2424-1970 |
| Download PDF |
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| Conference Information |
| Committee |
IEICE-CQ IEE-CMN BCT |
| Conference Date |
2025-11-06 - 2025-11-07 |
| Place (in Japanese) |
(See Japanese page) |
| Place (in English) |
Tokimate |
| Topics (in Japanese) |
(See Japanese page) |
| Topics (in English) |
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| Paper Information |
| Registration To |
IEICE-CQ |
| Conference Code |
2025-11-CQ-CMN-BCT |
| Language |
English |
| Title (in Japanese) |
(See Japanese page) |
| Sub Title (in Japanese) |
(See Japanese page) |
| Title (in English) |
Intelligent Training Control for Hierarchical Federated Learning in Dynamic Vehicular Environments |
| Sub Title (in English) |
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| Keyword(1) |
Federated Learning |
| Keyword(2) |
Internet of Vehicles |
| Keyword(3) |
Deep Reinforcement Learning |
| Keyword(4) |
DQN |
| Keyword(5) |
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| Keyword(6) |
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| 1st Author's Name |
Zhaoyang Du |
| 1st Author's Affiliation |
The University of Electro-Communications (UEC) |
| 2nd Author's Name |
Celimuge Wu |
| 2nd Author's Affiliation |
The University of Electro-Communications (UEC) |
| 3rd Author's Name |
Yangfei Lin |
| 3rd Author's Affiliation |
The University of Electro-Communications (UEC) |
| 4th Author's Name |
Jiale Wu |
| 4th Author's Affiliation |
The University of Electro-Communications (UEC) |
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| Speaker |
Author-1 |
| Date Time |
2025-11-06 14:55:00 |
| Presentation Time |
25 minutes |
| Registration for |
IEICE-CQ |
| Paper # |
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| Volume (vol) |
vol.49 |
| Number (no) |
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| Page |
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