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Paper Abstract and Keywords
Presentation 2018-02-26 14:25
Evaluation of Mobile Data Offloading Method Using Deep Reinforcement Learning
Daisuke Mochizuki, Yu Abiko (Shizuoka Univ.), Takato Saito, Masaji Katagiri, Daizo Ikeda (NTT DOCOMO), Hiroshi Mineno (Shizuoka Univ.) MoNA2017-65
Abstract (in Japanese) (See Japanese page) 
(in English) In recent years, the demand for mobile data communication has been increasing as the technologies of IoT have been widely used, and it is known that the mobile data traffic has a locality in commuting time and urban areas. There is a problem that the cellular infrastructures are crowded and the mobile data communication demand makes the network accommodation efficiency lower. As a method for improving the cellular infrastructures bandwidth utilization efficiency, a transmission rate control method has been proposed such as MDOP which balances the load by focus on the delay tolerance of contents. However, mathematical models do not have perform well to maximize bandwidth utilization efficiency in various situations. In this paper, to improve bandwidth utilization efficiency, we propose mobile data offloading method using deep reinforcement learning considering the delay tolerance of contents. The proposal method can control transmission appropriately in situations where mathematical models do not work well. As a result, we confirmed that the proposal method reduces the excess data amount by 26% from the control target value compared to the time offloading of MDOP.
Keyword (in Japanese) (See Japanese page) 
(in English) Offloading / Reinforcement Learning / Delay Tolerant / Mobile Data / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 450, MoNA2017-65, pp. 141-146, Feb. 2018.
Paper # MoNA2017-65 
Date of Issue 2018-02-19 (MoNA) 
ISSN Print edition: ISSN 0913-5685    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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Conference Information
Committee MoNA ASN IPSJ-MBL IPSJ-UBI  
Conference Date 2018-02-26 - 2018-02-27 
Place (in Japanese) (See Japanese page) 
Place (in English) Sophia University 
Topics (in Japanese) (See Japanese page) 
Topics (in English) Ubiquitous system, Ambient intelligence, Next generation wireless communicasion, Mobile network, etc. 
Paper Information
Registration To MoNA 
Conference Code 2018-02-MoNA-ASN-MBL-UBI 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Evaluation of Mobile Data Offloading Method Using Deep Reinforcement Learning 
Sub Title (in English)  
Keyword(1) Offloading  
Keyword(2) Reinforcement Learning  
Keyword(3) Delay Tolerant  
Keyword(4) Mobile Data  
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Keyword(6)  
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1st Author's Name Daisuke Mochizuki  
1st Author's Affiliation Shizuoka University (Shizuoka Univ.)
2nd Author's Name Yu Abiko  
2nd Author's Affiliation Shizuoka University (Shizuoka Univ.)
3rd Author's Name Takato Saito  
3rd Author's Affiliation NTT DOCOMO,Inc. (NTT DOCOMO)
4th Author's Name Masaji Katagiri  
4th Author's Affiliation NTT DOCOMO,Inc. (NTT DOCOMO)
5th Author's Name Daizo Ikeda  
5th Author's Affiliation NTT DOCOMO,Inc. (NTT DOCOMO)
6th Author's Name Hiroshi Mineno  
6th Author's Affiliation Shizuoka University (Shizuoka Univ.)
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Speaker Author-1 
Date Time 2018-02-26 14:25:00 
Presentation Time 25 minutes 
Registration for MoNA 
Paper # MoNA2017-65 
Volume (vol) vol.117 
Number (no) no.450 
Page pp.141-146 
#Pages 6 
Date of Issue 2018-02-19 (MoNA) 

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