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Paper Abstract and Keywords
Presentation 2018-03-01 09:00
Predictive traffic engineering incorporating real-world information inspired by human brain cognition process
Kodai Satake, Yuichi Ohsita, Masayuki Murata (Osaka Univ.) IN2017-93
Abstract (in Japanese) (See Japanese page) 
(in English) The amount of traffic through networks is increasing both in quantity and in fluctuation.
One approach to accommodating such fluctuating traffic is to dynamically control resources in a network based on the predicted traffic. In this approach, the accuracy of the prediction is important. There are many methods to predict future traffic. Most of them predict the future traffic from the traffic rates of the previous time slots. However, it is difficult for these methods to predict future traffic accurately, because the traffic is affected by the human behavior, and the sign of the traffic change may not be included in the past traffic data.
In this paper, we discuss the predictive traffic engineering methods using both of the monitored traffic data and real-world information. In this method, we need to decide the amount of resources based on the monitored traffic and real-world information, whose relation to the future traffic is unclear.
In this paper, we apply a mechanism of human brain, which makes decisions from uncertain and incomplete information, to making decisions in the predicted traffic engineering.
Through simulations, we demonstrate that our method avoid congestions without allocating a large amount of resources.
Keyword (in Japanese) (See Japanese page) 
(in English) Traffic Engineering / Resource Allocation / Real-World Information / Human Brain Cognition / / / /  
Reference Info. IEICE Tech. Rep., vol. 117, no. 460, IN2017-93, pp. 21-26, March 2018.
Paper # IN2017-93 
Date of Issue 2018-02-22 (IN) 
ISSN Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
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. (No. 10GA0019/12GB0052/13GB0056/17GB0034/18GB0034)
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Conference Information
Committee NS IN  
Conference Date 2018-03-01 - 2018-03-02 
Place (in Japanese) (See Japanese page) 
Place (in English) Phoenix Seagaia Resort 
Topics (in Japanese) (See Japanese page) 
Topics (in English) General 
Paper Information
Registration To IN 
Conference Code 2018-03-NS-IN 
Language Japanese 
Title (in Japanese) (See Japanese page) 
Sub Title (in Japanese) (See Japanese page) 
Title (in English) Predictive traffic engineering incorporating real-world information inspired by human brain cognition process 
Sub Title (in English)  
Keyword(1) Traffic Engineering  
Keyword(2) Resource Allocation  
Keyword(3) Real-World Information  
Keyword(4) Human Brain Cognition  
1st Author's Name Kodai Satake  
1st Author's Affiliation Osaka University (Osaka Univ.)
2nd Author's Name Yuichi Ohsita  
2nd Author's Affiliation Osaka University (Osaka Univ.)
3rd Author's Name Masayuki Murata  
3rd Author's Affiliation Osaka University (Osaka Univ.)
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Date Time 2018-03-01 09:00:00 
Presentation Time 20 
Registration for IN 
Paper # IEICE-IN2017-93 
Volume (vol) IEICE-117 
Number (no) no.460 
Page pp.21-26 
#Pages IEICE-6 
Date of Issue IEICE-IN-2018-02-22 

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