Presentation | 2023-01-19 [Short Paper] A Study of Joint Control Method of Wireless LAN and Machine Learning Settings for Communication-efficient Split Computing Kojin Yorita, Takayuki Nishio, Daiki Yoda, Toshihisa Nabetani, |
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PDF Download Page | PDF download Page Link |
Abstract(in Japanese) | (See Japanese page) |
Abstract(in English) | Split computing (SC) enables machine learning (ML) inference with a deep neural network on resource-constrained devices. However, a narrow-bandwidth and lossy wireless network can become a bottleneck, thereby increasing communication latency in SC due to retransmission and the use of lower physical transmission rate. To solve this trade-off between communication latency and inference accuracy, this paper studies a joint control of the wireless communication parameters (e.g., transmission rate, retransmission limit) and ML model to reduce communication latency and improve inference accuracy. The proposed method focuses on the packet-loss tolerance of ML inference and uses unreliable (i.e., high packet-loss rate) but low-latency communication protocol. To achieve a well-balanced trade-off between communication latency and inference accuracy, the proposed method jointly controls wireless communication parameters affecting the reliability and communication latency and ML model architecture affecting inference accuracy and packet-loss reliance, based on multi-armed bandit (MAB) algorithm, namely upper confidence bound (UCB) algorithm. The results of ns3-based computer simulations show that the proposed method reduces communication latency and improves inference accuracy. |
Keyword(in Japanese) | (See Japanese page) |
Keyword(in English) | Split computing / Joint control / Machine learning / Wireless LAN / Reinforcement Learning |
Paper # | SeMI2022-77 |
Date of Issue | 2023-01-12 (SeMI) |
Conference Information | |
Committee | SeMI |
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Conference Date | 2023/1/19(2days) |
Place (in Japanese) | (See Japanese page) |
Place (in English) | Naruto grand hotel |
Topics (in Japanese) | (See Japanese page) |
Topics (in English) | |
Chair | Koji Yamamoto(Kyoto Univ.) |
Vice Chair | Kazuya Monden(Hitachi) / Yasunori Owada(NICT) / Shunsuke Saruwatari(Osaka Univ.) |
Secretary | Kazuya Monden(NTT DOCOMO) / Yasunori Owada(Tokyo Univ. of Agri. and Tech.) / Shunsuke Saruwatari(Osaka Univ.) |
Assistant | Yuki Matsuda(NAIST) / Akihito Taya(Aoyama Gakuin Univ.) / Takeshi Hirai(Osaka Univ.) |
Paper Information | |
Registration To | Technical Committee on Sensor Network and Mobile Intelligence |
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Language | JPN |
Title (in Japanese) | (See Japanese page) |
Sub Title (in Japanese) | (See Japanese page) |
Title (in English) | [Short Paper] A Study of Joint Control Method of Wireless LAN and Machine Learning Settings for Communication-efficient Split Computing |
Sub Title (in English) | |
Keyword(1) | Split computing |
Keyword(2) | Joint control |
Keyword(3) | Machine learning |
Keyword(4) | Wireless LAN |
Keyword(5) | Reinforcement Learning |
1st Author's Name | Kojin Yorita |
1st Author's Affiliation | Tokyo Institute of Technology(Tokyo Tech) |
2nd Author's Name | Takayuki Nishio |
2nd Author's Affiliation | Tokyo Institute of Technology(Tokyo Tech) |
3rd Author's Name | Daiki Yoda |
3rd Author's Affiliation | Toshiba(Toshiba) |
4th Author's Name | Toshihisa Nabetani |
4th Author's Affiliation | Toshiba(Toshiba) |
Date | 2023-01-19 |
Paper # | SeMI2022-77 |
Volume (vol) | vol.122 |
Number (no) | SeMI-341 |
Page | pp.pp.28-29(SeMI), |
#Pages | 2 |
Date of Issue | 2023-01-12 (SeMI) |