Paper Abstract and Keywords |
Presentation |
2019-12-06 13:50
Performance Evaluation of Machine Learning Based Channel Selection Algorithm Implemented on IoT Sensor Devices and Its Application to Data Collection System for Building Monitoring So Hasegawa, Ryoma Kitagawa, Takumi Ito, Takashi Nakajima (TUS), Song-Ju Kim (KU), Yozo Shoji (NICT), Mikio Hasegawa (TUS) SR2019-106 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
The IoT wave have spread and the number of IoT devices have rapidly increased. Numerous IoT devices may generate enormous traffic, which may cause network congestions. To manage network congestions, we have proposed a channel selection algorithm based reinforcement learning for IoT devices with limited function. We have modeled channel allocation in IoT networks as Multi-Armed Bandit problem and have solved it by utilizing tug-of-war (TOW) dynamics. In this paper, we conduct evaluation experiment in a real environment where various IoT networks coexist. We clarify effectiveness of the proposed algorithm by evaluating the packet delivery rates (frame success rates) and fairness among the sensor nodes. Furthermore, we apply our proposed scheme to building monitoring system. We actually deploy the devices in a building and confirm collecting sensor data. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Machine Learning / Reinforcement Learning / Multi-Armed Bandit / IoT / Distributed Channel Selection / / / |
Reference Info. |
IEICE Tech. Rep., vol. 119, no. 325, SR2019-106, pp. 103-108, Dec. 2019. |
Paper # |
SR2019-106 |
Date of Issue |
2019-11-28 (SR) |
ISSN |
Online edition: ISSN 2432-6380 |
Copyright and reproduction |
All rights are reserved and no part of this publication may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording, or any information storage and retrieval system, without permission in writing from the publisher. Notwithstanding, instructors are permitted to photocopy isolated articles for noncommercial classroom use without fee. (License No.: 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034) |
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SR2019-106 |
Conference Information |
Committee |
SR |
Conference Date |
2019-12-05 - 2019-12-06 |
Place (in Japanese) |
(See Japanese page) |
Place (in English) |
Ishigaki City Hall (Ishigaki Island) |
Topics (in Japanese) |
(See Japanese page) |
Topics (in English) |
cognitive radio, machine learning application, heterogeneous network, SDN, IoT etc. |
Paper Information |
Registration To |
SR |
Conference Code |
2019-12-SR |
Language |
Japanese |
Title (in Japanese) |
(See Japanese page) |
Sub Title (in Japanese) |
(See Japanese page) |
Title (in English) |
Performance Evaluation of Machine Learning Based Channel Selection Algorithm Implemented on IoT Sensor Devices and Its Application to Data Collection System for Building Monitoring |
Sub Title (in English) |
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Keyword(1) |
Machine Learning |
Keyword(2) |
Reinforcement Learning |
Keyword(3) |
Multi-Armed Bandit |
Keyword(4) |
IoT |
Keyword(5) |
Distributed Channel Selection |
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1st Author's Name |
So Hasegawa |
1st Author's Affiliation |
Tokyo University of Science (TUS) |
2nd Author's Name |
Ryoma Kitagawa |
2nd Author's Affiliation |
Tokyo University of Science (TUS) |
3rd Author's Name |
Takumi Ito |
3rd Author's Affiliation |
Tokyo University of Science (TUS) |
4th Author's Name |
Takashi Nakajima |
4th Author's Affiliation |
Tokyo University of Science (TUS) |
5th Author's Name |
Song-Ju Kim |
5th Author's Affiliation |
Keio University (KU) |
6th Author's Name |
Yozo Shoji |
6th Author's Affiliation |
National Institute of Information and Communications Technology (NICT) |
7th Author's Name |
Mikio Hasegawa |
7th Author's Affiliation |
Tokyo University of Science (TUS) |
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Speaker |
Author-1 |
Date Time |
2019-12-06 13:50:00 |
Presentation Time |
25 minutes |
Registration for |
SR |
Paper # |
SR2019-106 |
Volume (vol) |
vol.119 |
Number (no) |
no.325 |
Page |
pp.103-108 |
#Pages |
6 |
Date of Issue |
2019-11-28 (SR) |
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