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| Presentation | 2020-03-06 14:00 Routing Design Method using Recurrent Deep Learning Model for Guaranteed Bandwidth Services Makoto Ito, Taiju Mikoshi, Katsunori Oyama, Toshihiro Nishizono (Nihon Univ.)  NS2019-240 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | This study proposes a novel routing design method using deep neural network for guaranteed bandwidth services. The proposed method uses recurrent neural network for improving the path calculation success rate and processing the entire traffic demand. The input to the learning model is the source-destination pair information and the required bandwidth arranged in descending order. The output is path information between source-destination pairs. The proposed method used, as teacher data, the minimum cost path obtained by the Dijkstra method using inverse of the remaining bandwidths as link costs. From the evaluation result, the proposed method improves the calculation time of the path to satisfy the bandwidth guaranteed in comparison with the Dijkstra method. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Guaranteed Bandwidth Service / Path Planning / Deep Learning / Recurrent Neural Network / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 119, no. 460, NS2019-240, pp. 353-358, March 2020. | |
| Paper # | NS2019-240 | |
| Date of Issue | 2020-02-27 (NS) | |
| 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 | NS2019-240 |
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| Conference Information | |
| Committee | NS IN |
| Conference Date | 2020-03-05 - 2020-03-06 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Royal Hotel Okinawa Zanpa-Misaki |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | General |
| Paper Information | |
| Registration To | NS |
| Conference Code | 2020-03-NS-IN |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Routing Design Method using Recurrent Deep Learning Model for Guaranteed Bandwidth Services |
| Sub Title (in English) | |
| Keyword(1) | Guaranteed Bandwidth Service |
| Keyword(2) | Path Planning |
| Keyword(3) | Deep Learning |
| Keyword(4) | Recurrent Neural Network |
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| 1st Author's Name | Makoto Ito |
| 1st Author's Affiliation | Nihon University (Nihon Univ.) |
| 2nd Author's Name | Taiju Mikoshi |
| 2nd Author's Affiliation | Nihon University (Nihon Univ.) |
| 3rd Author's Name | Katsunori Oyama |
| 3rd Author's Affiliation | Nihon University (Nihon Univ.) |
| 4th Author's Name | Toshihiro Nishizono |
| 4th Author's Affiliation | Nihon University (Nihon Univ.) |
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| Speaker | Author-1 |
| Date Time | 2020-03-06 14:00:00 |
| Presentation Time | 20 minutes |
| Registration for | NS |
| Paper # | NS2019-240 |
| Volume (vol) | vol.119 |
| Number (no) | no.460 |
| Page | pp.353-358 |
| #Pages | 6 |
| Date of Issue | 2020-02-27 (NS) |
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