Presentation 2023-08-31
Enhancing Communication Efficiency for UAV Networks through Knowledge Distillation and Transfer Learning in Federated Learning
Yalong Li, Zhaoyang Du, Celimuge Wu, Tsutomu Yoshinaga,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Federated learning (FL) in unmanned aerial vehicles (UAVs) networks demands considerable communication resources to transfer model data between the central server and UAVs (FL clients). However, different UAVs may have different communication capabilities due to the UAV's maneuverability and heterogeneity, where limited communication resource could be bottle neck for FL performance. In this paper, we first introduce a knowledge distillation based approach that places two different models with different sizes, namely the teacher model and student model, for FL client to make a trade-off between the FL performance and communication cost. Then, we propose a novel model switching method to switch between the teacher model and student model to adapt to the dynamic feature of UAV networks. Specifically, considering available communication bandwidth and learning accuracy, we design a threshold-based model switching algorithm (TBMSA) and determine the threshold based on the k-means method (DTBKM) to accurately and quickly determine the switching point. In addition, for the knowledge transfer between models, we design a knowledge inheritance based on a transfer learning (KIBTL) algorithm, which transfers knowledge from one model to another. Experiments show that the proposed model switching algorithm achieves significant performance improvements as compared to existing baselines.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) UAV Networks / Federated Learning / Model Switching / Knowledge Distillation / Transfer Learning
Paper # CQ2023-30
Date of Issue 2023-08-24 (CQ)

Conference Information
Committee CQ
Conference Date 2023/8/31(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Tenjin-Misaki Sports Park
Topics (in Japanese) (See Japanese page)
Topics (in English) Wireless Communications Quality, 6G, IoT, Resource Management, Wireless Transmission, Cross layer Technologies, etc.
Chair Takefumi Hiraguri(Nippon Inst. of Tech.)
Vice Chair Takahiro Matsuda(Tokyo Metropolitan Univ.) / Gou Hasegawa(Tohoku Univ.) / Sumaru Niida(KDDI Research)
Secretary Takahiro Matsuda(NTT) / Gou Hasegawa(Tama Univ.) / Sumaru Niida(Tsukuba Univ.)
Assistant Ryo Nakamura(Fukuoka Univ.) / Toshiro Nakahira(NTT) / Kenta Tsukatsune(Okayama Univ. of Science)

Paper Information
Registration To Technical Committee on Communication Quality
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Enhancing Communication Efficiency for UAV Networks through Knowledge Distillation and Transfer Learning in Federated Learning
Sub Title (in English)
Keyword(1) UAV Networks
Keyword(2) Federated Learning
Keyword(3) Model Switching
Keyword(4) Knowledge Distillation
Keyword(5) Transfer Learning
1st Author's Name Yalong Li
1st Author's Affiliation the university of electro-communications(UEC)
2nd Author's Name Zhaoyang Du
2nd Author's Affiliation the university of electro-communications(UEC)
3rd Author's Name Celimuge Wu
3rd Author's Affiliation the university of electro-communications(UEC)
4th Author's Name Tsutomu Yoshinaga
4th Author's Affiliation the university of electro-communications(UEC)
Date 2023-08-31
Paper # CQ2023-30
Volume (vol) vol.123
Number (no) CQ-174
Page pp.pp.26-31(CQ),
#Pages 6
Date of Issue 2023-08-24 (CQ)