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Paper Abstract and Keywords
Presentation 2022-10-14 10:40
[Poster Presentation] Reinforcement Learning-based Method for Reducing Power Consumption of BLE Advertisements
Minoru Fujisawa (Tokyo Univ. of Science), Hiroyuki Yasuda (The Univ. of Tokyo), Ryosuke Isogai, Yoshifumi Yoshida (SEIKO FUTURE CREATION INC.), Song-Ju Kim (SOBIN Inst.), Mikio Hasegawa (Tokyo Univ. of Science)
Abstract (in Japanese) (See Japanese page) 
(in English) Bluetooth Low Energy (BLE) has been applied to various IoT applications due to the popularization of Bluetooth-enabled devices and their low power consumption. However, by efficiently selecting the advertising interval and channels, it is possible to achieve even lower power consumption. We have proposed an efficient selection method based on the Multi-Armed Bandit (MAB) algorithms by considering the wireless environment for channels and advertising intervals. In this paper, we evaluate the proposed method by simulations under various environments. The results show that the proposed method can reduce power consumption according to the wireless environment without significant loss of reliability.
Keyword (in Japanese) (See Japanese page) 
(in English) IoT / Reinforcement learning / Bluetooth Low Energy / BLE advertising / Multi-Armed Bandit problem / / /  
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Conference Information
Committee MIKA  
Conference Date 2022-10-12 - 2022-10-15 
Place (in Japanese) (See Japanese page) 
Place (in English) Niigata Citizens Plaza 
Topics (in Japanese) (See Japanese page) 
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Paper Information
Registration To MIKA 
Conference Code 2022-10-MIKA 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Reinforcement Learning-based Method for Reducing Power Consumption of BLE Advertisements 
Sub Title (in English)  
Keyword(1) IoT  
Keyword(2) Reinforcement learning  
Keyword(3) Bluetooth Low Energy  
Keyword(4) BLE advertising  
Keyword(5) Multi-Armed Bandit problem  
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1st Author's Name Minoru Fujisawa  
1st Author's Affiliation Tokyo University of Science (Tokyo Univ. of Science)
2nd Author's Name Hiroyuki Yasuda  
2nd Author's Affiliation The University of Tokyo (The Univ. of Tokyo)
3rd Author's Name Ryosuke Isogai  
3rd Author's Affiliation SEIKO FUTURE CREATION INC. (SEIKO FUTURE CREATION INC.)
4th Author's Name Yoshifumi Yoshida  
4th Author's Affiliation SEIKO FUTURE CREATION INC. (SEIKO FUTURE CREATION INC.)
5th Author's Name Song-Ju Kim  
5th Author's Affiliation SOBIN Institute LLC. (SOBIN Inst.)
6th Author's Name Mikio Hasegawa  
6th Author's Affiliation Tokyo University of Science (Tokyo Univ. of Science)
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Speaker Author-1 
Date Time 2022-10-14 10:40:00 
Presentation Time 50 minutes 
Registration for MIKA 
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