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Paper Abstract and Keywords
Presentation 2016-01-22 15:50
Reinforcement learning-based parameter tuning for a broadcast protocol in VANETs
Celimuge Wu, Satoshi Ohzahata (UEC), Yusheng Ji (NII), Tsutomu Yoshinaga, Toshihiko Kato (UEC) CQ2015-105
Abstract (in Japanese) (See Japanese page) 
(in English) It is particularly challenging to design an intelligent multi-hop broadcast protocol for vehicular ad hoc networks (VANETs) due to the dynamic environment. Existing protocols are optimized for a specific scenario, and are not capable of working in various scenarios. In this paper, we present a broadcast protocol which is able to make forwarding decision based on a self-learning mechanism. The protocol employs a fuzzy logic-based relay node selection approach to take into account multiple metrics for the forwarding algorithm. The parameters used for the fuzzy logic are tuned online using a reinforcement learning approach. The combination of reinforcement learning and fuzzy logic can provide an intelligent solution for broadcasting in VANETs. We conduct computer simulations to evaluate the proposed protocol.
Keyword (in Japanese) (See Japanese page) 
(in English) VANETs / Multi-hop broadcast / Fuzzy logic / Reinforcement learning / / / /  
Reference Info. IEICE Tech. Rep., vol. 115, no. 408, CQ2015-105, pp. 73-78, Jan. 2016.
Paper # CQ2015-105 
Date of Issue 2016-01-14 (CQ) 
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 CQ2015-105

Conference Information
Committee CQ  
Conference Date 2016-01-21 - 2016-01-22 
Place (in Japanese) (See Japanese page) 
Place (in English) University of Tsukuba 
Topics (in Japanese) (See Japanese page) 
Topics (in English)  
Paper Information
Registration To CQ 
Conference Code 2016-01-CQ 
Language English 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Reinforcement learning-based parameter tuning for a broadcast protocol in VANETs 
Sub Title (in English)  
Keyword(1) VANETs  
Keyword(2) Multi-hop broadcast  
Keyword(3) Fuzzy logic  
Keyword(4) Reinforcement learning  
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1st Author's Name Celimuge Wu  
1st Author's Affiliation The University of Electro-Communications (UEC)
2nd Author's Name Satoshi Ohzahata  
2nd Author's Affiliation The University of Electro-Communications (UEC)
3rd Author's Name Yusheng Ji  
3rd Author's Affiliation National Institute of Informatics (NII)
4th Author's Name Tsutomu Yoshinaga  
4th Author's Affiliation The University of Electro-Communications (UEC)
5th Author's Name Toshihiko Kato  
5th Author's Affiliation The University of Electro-Communications (UEC)
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Speaker Author-1 
Date Time 2016-01-22 15:50:00 
Presentation Time 25 minutes 
Registration for CQ 
Paper # CQ2015-105 
Volume (vol) vol.115 
Number (no) no.408 
Page pp.73-78 
#Pages 6 
Date of Issue 2016-01-14 (CQ) 

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