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| Presentation | 2018-12-13 14:45 Towards application of network topology information to network log causal anlaysis Satoru Kobayashi (NII), Kazuki Otomo (Univ. Tokyo), Kensuke Fukuda (NII)  IA2018-40 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | To detect root causes of failures in large-scale networks, we need to extract contextual information from operational data automatically. Causal inference is one of the approaches to achieve it, but has a problem of enormous processing time with large-scale data. In this research, we propose a preprocessing method for PC algorithm, a causal structure estimation algorithm based on causal inference. We prune self-evidently failure causal edges from initial graph with a prior knowledge of network topology. With this preprocessing, we decrease 25% processing time of causal structure estimation of log data in nation-wide R&E network. We also show our method detects more useful information for troubleshooting compared to area-based existing method. | |
| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | System log / Causal inference / Pruning / Network topology / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 118, no. 360, IA2018-40, pp. 1-8, Dec. 2018. | |
| Paper # | IA2018-40 | |
| Date of Issue | 2018-12-06 (IA) | |
| 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 | IA2018-40 |
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| Conference Information | |
| Committee | IA IN |
| Conference Date | 2018-12-13 - 2018-12-14 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Hiroshima Univ. |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | Performance Analysis and Simulation, Robustness, Traffic and Throughput Measurement, Quality of Service (QoS) Control, Congestion Control, Overlay Network/P2P, IPv6, Multicast, Routing, DDoS, etc. |
| Paper Information | |
| Registration To | IA |
| Conference Code | 2018-12-IA-IN |
| Language | Japanese |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | Towards application of network topology information to network log causal anlaysis |
| Sub Title (in English) | |
| Keyword(1) | System log |
| Keyword(2) | Causal inference |
| Keyword(3) | Pruning |
| Keyword(4) | Network topology |
| Keyword(5) | |
| Keyword(6) | |
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| Keyword(8) | |
| 1st Author's Name | Satoru Kobayashi |
| 1st Author's Affiliation | National Institute of Informatics (NII) |
| 2nd Author's Name | Kazuki Otomo |
| 2nd Author's Affiliation | The university of Tokyo (Univ. Tokyo) |
| 3rd Author's Name | Kensuke Fukuda |
| 3rd Author's Affiliation | National Institute of Informatics (NII) |
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| Speaker | Author-1 |
| Date Time | 2018-12-13 14:45:00 |
| Presentation Time | 25 minutes |
| Registration for | IA |
| Paper # | IA2018-40 |
| Volume (vol) | vol.118 |
| Number (no) | no.360 |
| Page | pp.1-8 |
| #Pages | 8 |
| Date of Issue | 2018-12-06 (IA) |
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