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Paper Abstract and Keywords
Presentation 2011-03-03 10:00
A Study on Reinforcement Learning for Improving Fairness in Lightpath Networks
Shu Kobuchi, Takuji Tachibana (NAIST), Sugang Xu (NICT) NS2010-167
Abstract (in Japanese) (See Japanese page) 
(in English) In lightpath networks, lightpaths whose number of hops is large are not established easily than those whose number of hops is small. This causes the unfairness of the lightpath establishment in terms of lightpath blocking probability. Especially, in a distributed control environment without a central server, it is not easy to resolve such a unfairness. Therefore, we propose a dynamic lightpath establishment with reinforcement learning and Bayesian estimation so as to improve the fairness. In our proposed method, when a node receives a lightpath establishment request, it estimates the total number of hops between source and destination nodes by using Bayesian estimation. Then, the node accepts or rejects the request from the estimated number of transmission hops by using reinforcement learning. In this reinforcement learning, a node obtains a larger reward for the establishment of a large-hop lightpath. Therefore, it is expected that the fairness can be improved by using the proposed method. We evaluate the performance of our proposed method with simulation, and we investigate the effectiveness of the method.
Keyword (in Japanese) (See Japanese page) 
(in English) Lightpath establishment / Reinforcement learning / Q-learning / Bayesian estimation / Fairness / / /  
Reference Info. IEICE Tech. Rep., vol. 110, no. 448, NS2010-167, pp. 25-28, March 2011.
Paper # NS2010-167 
Date of Issue 2011-02-24 (NS) 
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)
Download PDF NS2010-167

Conference Information
Committee IN NS  
Conference Date 2011-03-03 - 2011-03-04 
Place (in Japanese) (See Japanese page) 
Place (in English) Okinawa Convention Center 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General, NS+IN workshop (March 3-4) 
Paper Information
Registration To NS 
Conference Code 2011-03-IN-NS 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) A Study on Reinforcement Learning for Improving Fairness in Lightpath Networks 
Sub Title (in English)  
Keyword(1) Lightpath establishment  
Keyword(2) Reinforcement learning  
Keyword(3) Q-learning  
Keyword(4) Bayesian estimation  
Keyword(5) Fairness  
Keyword(6)  
Keyword(7)  
Keyword(8)  
1st Author's Name Shu Kobuchi  
1st Author's Affiliation Nara Institute of Science and Technology (NAIST)
2nd Author's Name Takuji Tachibana  
2nd Author's Affiliation Nara Institute of Science and Technology (NAIST)
3rd Author's Name Sugang Xu  
3rd Author's Affiliation National Institute of Information and Communications Technology (NICT)
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Speaker Author-1 
Date Time 2011-03-03 10:00:00 
Presentation Time 20 minutes 
Registration for NS 
Paper # NS2010-167 
Volume (vol) vol.110 
Number (no) no.448 
Page pp.25-28 
#Pages 4 
Date of Issue 2011-02-24 (NS) 

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