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| Presentation | 2018-01-18 13:35 Numerical Evaluation of Cooperative Edge System for Realtime Predictive Information Delivery MAsahiro Kanbayashi, Shingo Kato, Ryoichi Shinkuma (Kyoto Univ.)  MoNA2017-42 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Traffic congestion is still a serious social problem in the recent years.Predictive road traffic information delivery is expected as a promising solution for the problem.When machine learning is used to predict road traffic, computing resources in edge and cloud servers should be cooperatively leveraged to ensure realtime delivery of information.However, prior works related to edge-cloud cooperation did not consider the fact that the amount of sensor data collected and processed at edge servers is geographically different area-by-area.Therefore, this report proposes an edge cooperation system for realtime delivery of predictive road traffic information.We tackle a mathematical problem formulation as a generalized mutual assignment problem for maximizing prediction accuracy while considering the latency requirement for realtime delivery . As the first step of our work, we consider the system that consists of two edge servers and discuss the performance evaluation with the scenario where roadside cameras work for collecting road-traffic information as sensors in the system. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | edge computing / road traffic prediction / machine learning / realtime delivery / generalized mutual assignment problem / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 117, no. 390, MoNA2017-42, pp. 7-12, Jan. 2018. | |
| Paper # | MoNA2017-42 | |
| Date of Issue | 2018-01-11 (MoNA) | |
| 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 | MoNA2017-42 |
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| Conference Information | |
| Committee | MoNA |
| Conference Date | 2018-01-18 - 2018-01-19 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Campus Plaza Kyoto |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Mobile Network, Application of Machine Learning, Mobile Data, etc. |
| Paper Information | |
| Registration To | MoNA |
| Conference Code | 2018-01-MoNA |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Numerical Evaluation of Cooperative Edge System for Realtime Predictive Information Delivery |
| Sub Title (in English) | |
| Keyword(1) | edge computing |
| Keyword(2) | road traffic prediction |
| Keyword(3) | machine learning |
| Keyword(4) | realtime delivery |
| Keyword(5) | generalized mutual assignment problem |
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| Keyword(7) | |
| Keyword(8) | |
| 1st Author's Name | MAsahiro Kanbayashi |
| 1st Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 2nd Author's Name | Shingo Kato |
| 2nd Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 3rd Author's Name | Ryoichi Shinkuma |
| 3rd Author's Affiliation | Kyoto University (Kyoto Univ.) |
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| Speaker | Author-1 |
| Date Time | 2018-01-18 13:35:00 |
| Presentation Time | 25 minutes |
| Registration for | MoNA |
| Paper # | MoNA2017-42 |
| Volume (vol) | vol.117 |
| Number (no) | no.390 |
| Page | pp.7-12 |
| #Pages | 6 |
| Date of Issue | 2018-01-11 (MoNA) |
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