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Paper Abstract and Keywords
Presentation 2024-11-11 13:20
[Poster Presentation] Parameter Aggregation Timing Control in Vehicular Federated Learning
Shota Ono, Akihiro Nakao (The Univ. of Tokyo)
Abstract (in Japanese) (See Japanese page) 
(in English) Autonomous driving systems encounter challenges related to privacy and the handling of large amounts of data during the learning process. Vehicular Federated Learning (VFL) addresses these challenges by privacy protection and reducing data transmission volume. However, conventional VFL methods do not consider real-world factors such as client mobility and Roadside Unit (RSU) timeouts. When clients move out of the RSU‘s coverage, model updates are interrupted, and learning efficiency decreases. This paper proposes the Adaptive Timing Control method to optimize the transmission of client model gradients in VFL. The proposed method enables gradient aggregation regardless of RSU timeouts or client movement. Clients can upload gradients before leaving the RSU’s coverage, even if the learning process is not completed. The proposed method reduces transmission volume by approximately 124 times compared to sending raw data and doubles learning efficiency. These results demonstrate the effectiveness of the proposed method in autonomous driving systems in real-world environments.
Keyword (in Japanese) (See Japanese page) 
(in English) Federated learning / Parameter aggregation timing / Mobility service / / / / /  
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Conference Information
Committee RISING  
Conference Date 2024-11-11 - 2024-11-12 
Place (in Japanese) (See Japanese page) 
Place (in English) Kaderu 2・7 (Sapporo) 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Cross-Field Research Association of Super-Intelligent Networking 
Paper Information
Registration To RISING 
Conference Code 2024-11-RISING 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Parameter Aggregation Timing Control in Vehicular Federated Learning 
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Keyword(1) Federated learning  
Keyword(2) Parameter aggregation timing  
Keyword(3) Mobility service  
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1st Author's Name Shota Ono  
1st Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
2nd Author's Name Akihiro Nakao  
2nd Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
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Speaker Author-1 
Date Time 2024-11-11 13:20:00 
Presentation Time 50 minutes 
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