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| Presentation | 2022-01-24 16:20 Channel Selection of Environment-Adaptive Sensor Networks Using Channel Occupancy Rate Taiki Matsushima, Takeo Fujii (UEC)  SR2021-65 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | In Wireless Sensor Networks (WSNs), it is possible to transmit packets efficiently by implementing an autonomous distributed channel selection method in which a Sensor Node (SN) selects the channel to be used by itself. In addition, autonomous distributed channel selection is modeled as a Multi-Armed Bandit (MAB) problem, and execution of channel selection based on Tug-of-War (TOW) dynamics can achieve highly efficient learning with low computational complexity. On the other hand, channel selection based on TOW dynamics determines the reward only based on whether an Acknowledgement (ACK) frame is received, which means that the reward is determined without considering the environment surrounding the SN. In this paper, we propose an algorithm that determines the reward using the channel occupancy rate and existence of hidden terminals in addition to whether an ACK frame is received. The proposed algorithm calculates the most recent channel occupancy rate to determine the reward. Then, the reward is changed according to the calculated channel occupancy rate and the presence of hidden terminals. Simulation results show that the proposed method can adapt to rapidly changing environment and select the best channel compared to the method that determines the reward based only on whether an ACK frame is received. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Wireless Sensor Networks / Channel Selection / Multi-Armed Bandit Problem / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 121, no. 345, SR2021-65, pp. 31-36, Jan. 2022. | |
| Paper # | SR2021-65 | |
| Date of Issue | 2022-01-17 (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) | |
| Download PDF | SR2021-65 |
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| Conference Information | |
| Committee | SR |
| Conference Date | 2022-01-24 - 2022-01-25 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | SR |
| Conference Code | 2022-01-SR |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Channel Selection of Environment-Adaptive Sensor Networks Using Channel Occupancy Rate |
| Sub Title (in English) | |
| Keyword(1) | Wireless Sensor Networks |
| Keyword(2) | Channel Selection |
| Keyword(3) | Multi-Armed Bandit Problem |
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| 1st Author's Name | Taiki Matsushima |
| 1st Author's Affiliation | The University of Electro-Communications (UEC) |
| 2nd Author's Name | Takeo Fujii |
| 2nd Author's Affiliation | The University of Electro-Communications (UEC) |
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| Speaker | Author-1 |
| Date Time | 2022-01-24 16:20:00 |
| Presentation Time | 25 minutes |
| Registration for | SR |
| Paper # | SR2021-65 |
| Volume (vol) | vol.121 |
| Number (no) | no.345 |
| Page | pp.31-36 |
| #Pages | 6 |
| Date of Issue | 2022-01-17 (SR) |
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