Paper Abstract and Keywords |
Presentation |
2023-03-16 09:10
Network Recovery Planning Support Technology for Large-scale Disaster Kazuaki Akashi, Mayu Yamazoe, Hiroaki Matsubayashi, Shunsuke Kanai, Masashi Kobayashi, Kenichi Tayama (NTT) ICM2022-44 |
Abstract |
(in Japanese) |
(See Japanese page) |
(in English) |
Early recovery of communication services for large-scale disasters is an important social issue. Since it is not possible to repair all damaged facilities at once, telecommunications carriers should give priority to repairing facilities that are effective for recovery services. In this paper, we propose a method to support the recovery planning that minimize the impact on communication services by utilizing network resource management technology that enables the centralized management of multi-layer networks. The proposed method estimates the impact of each damaged facility on telecommunication services and generates a plan that prioritizes the facilities with the higher impact. We evaluate the proposed method as a use case for planning the deployment of mobile power supply vehicles for a wide-area blackout, and show that the proposed method is capable of generating a plan that reduces the service impact by about 41% compared to the case where the network configuration is not taken into account. |
Keyword |
(in Japanese) |
(See Japanese page) |
(in English) |
Network / Disaster Recovery / Progressive network recovery / / / / / |
Reference Info. |
IEICE Tech. Rep., vol. 122, no. 442, ICM2022-44, pp. 1-6, March 2023. |
Paper # |
ICM2022-44 |
Date of Issue |
2023-03-09 (ICM) |
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) |
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ICM2022-44 |
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