Presentation | 2022-09-15 DRL-assisted Network Selection for Federated Learning Ganggui Wang, Celimuge Wu, Tsutomu Yoshinaga, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Recently, with the development of wireless communication technologies such as 5G, more and more devices communicate through wireless networks. Devices participating in federated learning will not be an exception. The performance of federated learning based on wireless communication is bound to be affected by the wireless communication environment. We discuss network selection for federated learning devices that can use different types of networks, including mmWave, and propose a deep reinforcement learning-based algorithm. The relationship among federated learning, wireless network, and deep reinforcement learning is considered. Finally, we analyze the results of computer simulation and evaluate the proposed algorithm. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Federated LearningReinforcement LearningWireless CommunicationMillimeter Wave |
Paper # | CQ2022-34 |
Date of Issue | 2022-09-08 (CQ) |
Conference Information | |
Committee | IA / CQ |
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Conference Date | 2022/9/15(2days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Hokkaido Citizens Actives Center |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | Wireless Communications Quality, 6G, IoT, Cross layer Technologies, Internet Operation and Management, etc. |
Chair | Tomoki Yoshihisa(Osaka Univ.) / Jun Okamoto(NTT) |
Vice Chair | Yusuke Sakumoto(Kwansei Gakuin Univ.) / Yuichiro Hei(KDDI Research) / Hiroshi Yamamoto(Ritsumeikan Univ.) / Takefumi Hiraguri(Nippon Inst. of Tech.) / Gou Hasegawa(Tohoku Univ.) |
Secretary | Yusuke Sakumoto(Osaka Univ.) / Yuichiro Hei(Kogakuin Univ.) / Hiroshi Yamamoto(Kyushu Inst. of Tech.) / Takefumi Hiraguri(NTT) / Gou Hasegawa(Ritsumeikan Univ.) |
Assistant | Daisuke Kotani(Kyoto Univ.) / Ryo Nakamura(Fukuoka Univ.) / Ryo Nakamura(Univ. of Tokyo) / Kimiko Kawashima(NTT) / Ryo Nakamura(Fukuoka Univ.) / Toshiro Nakahira(NTT) / Kenta Tsukatsune(Tokyo Metroplitan Univ.) |
Paper Information | |
Registration To | Technical Committee on Internet Architecture / Technical Committee on Communication Quality |
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Language | ENG |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | DRL-assisted Network Selection for Federated Learning |
Sub Title (in English) | |
Keyword(1) | Federated LearningReinforcement LearningWireless CommunicationMillimeter Wave |
1st Author's Name | Ganggui Wang |
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 | Tsutomu Yoshinaga |
3rd Author's Affiliation | The University of Electro-Communications(UEC) |
Date | 2022-09-15 |
Paper # | CQ2022-34 |
Volume (vol) | vol.122 |
Number (no) | CQ-184 |
Page | pp.pp.56-61(CQ), |
#Pages | 6 |
Date of Issue | 2022-09-08 (CQ) |