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| Presentation | 2019-01-17 10:30 Evaluation of Edge Cooperation Model for Real-Time Predictive Information Delivery Considering Prediction Accuracy Masahiro Kanbayashi, Ryoichi Shinkuma, Takehiro Sato, Eiji Oki (Kyoto Univ.)  MoNA2018-68 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Nowadays, traffic congestion is still a serious social problem in many countries. Real-time delivery of predictive road traffic information has been expected as a promising solution for the problem. Since the latency requirement is strict in such real-time delivery, edge cooperation has been studied to increase the capability of processing sensor data. However, although the prior works forced mainly on latency requirements, they did not consider the accuracy of predicted information. Therefore, this report proposes a model for edge cooperation. The edge cooperation system based on our model can maximize the prediction accuracy while satisfying the latency requirement for realtime delivery. Our model is formulated as a generalized mutual assignment problem, in which edge servers cooperatively process and use data that contribute to the improvement of prediction accuracy with high priority. This report considers a two edge-server case and discusses numerical evaluation with the scenario where roadside cameras work for collecting road-traffic information as sensors. From the numerical result, we validate the system based on our model in terms of prediction accuracy under various conditions. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | edge computing / machine learning / predictive information delivery / generalized mutual assignment problem / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 389, MoNA2018-68, pp. 63-68, Jan. 2019. | |
| Paper # | MoNA2018-68 | |
| Date of Issue | 2019-01-09 (MoNA) | |
| 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 | MoNA2018-68 |
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| Conference Information | |
| Committee | MoNA |
| Conference Date | 2019-01-16 - 2019-01-17 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | T. B. D. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | |
| Paper Information | |
| Registration To | MoNA |
| Conference Code | 2019-01-MoNA |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Evaluation of Edge Cooperation Model for Real-Time Predictive Information Delivery Considering Prediction Accuracy |
| Sub Title (in English) | |
| Keyword(1) | edge computing |
| Keyword(2) | machine learning |
| Keyword(3) | predictive information delivery |
| Keyword(4) | generalized mutual assignment problem |
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| 1st Author's Name | Masahiro Kanbayashi |
| 1st Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 2nd Author's Name | Ryoichi Shinkuma |
| 2nd Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 3rd Author's Name | Takehiro Sato |
| 3rd Author's Affiliation | Kyoto University (Kyoto Univ.) |
| 4th Author's Name | Eiji Oki |
| 4th Author's Affiliation | Kyoto University (Kyoto Univ.) |
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| Speaker | Author-1 |
| Date Time | 2019-01-17 10:30:00 |
| Presentation Time | 25 minutes |
| Registration for | MoNA |
| Paper # | MoNA2018-68 |
| Volume (vol) | vol.118 |
| Number (no) | no.389 |
| Page | pp.63-68 |
| #Pages | 6 |
| Date of Issue | 2019-01-09 (MoNA) |
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