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| Presentation | 2017-11-17 15:00 [Encouragement Talk] Reinforcement Learning based Automated Process Generation for Virtual Network Update Manabu Nakanoya (NEC)  ICM2017-32 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Spreading the network virtualization and softwarization technology using network function virtualization(NFV) and software-defined networking(SDN), provisioning automation software which has control functions for virtualized network functions(VNFs) and SDN controllers is being developed. These software can easily collect various log data at once and change configurations. Therefore, users can utilize it to automate not only simple routine operation, but also for machine learning technology that can learn optimized operation and execute it. Especially, reinforcement learning, which can learn from large number of trials, has been studied to apply various cases because it became easy to execute many trials with software. However, existing automated IT resource control technologies using reinforcement learning are only for the cases where reduction of search space such as allocation of virtual machine, and search efficiency are easy. Hence, it is difficult to learn control tasks which may contain extensive search space such as IP address range. In this paper, I propose (1) a framework which can easily define and execute reinforcement learning with provisioning automation software and (2) a fast learning algorithm that can execute learning including parameters with vast choices where the efficient searching method is not trivial. In Addition, I evaluate its effectiveness through actual update task of virtual network devices executed on the framework (1). | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Reinforcement Learning / Virtual Network / Configuration Update / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 305, ICM2017-32, pp. 63-68, Nov. 2017. | |
| Paper # | ICM2017-32 | |
| Date of Issue | 2017-11-09 (ICM) | |
| 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 | ICM2017-32 |
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| Conference Information | |
| Committee | ICM CQ NS NV |
| Conference Date | 2017-11-16 - 2017-11-17 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | ICM |
| Conference Code | 2017-11-ICM-CQ-NS-NV |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Reinforcement Learning based Automated Process Generation for Virtual Network Update |
| Sub Title (in English) | |
| Keyword(1) | Reinforcement Learning |
| Keyword(2) | Virtual Network |
| Keyword(3) | Configuration Update |
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| 1st Author's Name | Manabu Nakanoya |
| 1st Author's Affiliation | NEC Corporation (NEC) |
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| Speaker | Author-1 |
| Date Time | 2017-11-17 15:00:00 |
| Presentation Time | 25 minutes |
| Registration for | ICM |
| Paper # | ICM2017-32 |
| Volume (vol) | vol.117 |
| Number (no) | no.305 |
| Page | pp.63-68 |
| #Pages | 6 |
| Date of Issue | 2017-11-09 (ICM) |
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