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| Presentation | 2020-10-01 16:25 [Poster Presentation] A Study on Topology Estimation from Observed Network Flows Keita Kitaura, Ryotaro Matsuo (Kwansei Gakuin Univ.), Ryo Nakamura (Fukuoka Univ.), Hiroyuki Ohsaki (Kwansei Gakuin Univ.)  IA2020-11 |
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| Abstract | (in Japanese) | (See Japanese page) |
| (in English) | Acquisition and estimation of topologies of large-scale evolving networks such as communication networks and social networks are not trivial because of their scale, complexity, and dynamics. In general, the topology of a communication network can be represented as a graph composed of many vertices and edges. A network topology estimation problem can be formulated as a graph topology estimation problem with limited knowledge on the graph. Network topology estimation problems include a range of variants depending on the data available, constraints, and the objective function. Network topology estimation problems can be classified into two categories: direct and indirect. In indirect network topology estimation problems, only information regarding the network topology to be estimated is known. In this paper, we propose an indirect network topology estimation method called TOPFLOW (network TOPology inference from FLOW sets), which estimates the topology of a network from the limited number of flow sets observed at measurement nodes in the network. Also, we extensively investigate the effectiveness of TOPFLOW through a number of experiments with diverse networks with different structures and scales. Our findings include that the estimation accuracy grows almost linearly as the ratio of measurement nodes increases in several network topologies. |
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| Keyword | (in Japanese) | (See Japanese page) |
| (in English) | Network Topology Inference / Observed Flows / Shortest Path / / / / / | |
| Reference Info. | IEICE Tech. Rep., vol. 120, no. 177, IA2020-11, pp. 31-31, Oct. 2020. | |
| Paper # | IA2020-11 | |
| Date of Issue | 2020-09-24 (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 | IA2020-11 |
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| Conference Information | |
| Committee | IA |
| Conference Date | 2020-10-01 - 2020-10-01 |
| Place (in Japanese) | (See Japanese page) |
| Place (in English) | Online |
| Topics (in Japanese) | (See Japanese page) |
| Topics (in English) | IA2020 - Workshop on Internet Architecture and Applications 2020 |
| Paper Information | |
| Registration To | IA |
| Conference Code | 2020-10-IA |
| Language | English |
| Title (in Japanese) | (See Japanese page) |
| Sub Title (in Japanese) | (See Japanese page) |
| Title (in English) | A Study on Topology Estimation from Observed Network Flows |
| Sub Title (in English) | |
| Keyword(1) | Network Topology Inference |
| Keyword(2) | Observed Flows |
| Keyword(3) | Shortest Path |
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| 1st Author's Name | Keita Kitaura |
| 1st Author's Affiliation | Kwansei Gakuin University (Kwansei Gakuin Univ.) |
| 2nd Author's Name | Ryotaro Matsuo |
| 2nd Author's Affiliation | Kwansei Gakuin University (Kwansei Gakuin Univ.) |
| 3rd Author's Name | Ryo Nakamura |
| 3rd Author's Affiliation | Fukuoka University (Fukuoka Univ.) |
| 4th Author's Name | Hiroyuki Ohsaki |
| 4th Author's Affiliation | Kwansei Gakuin University (Kwansei Gakuin Univ.) |
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| Speaker | Author-1 |
| Date Time | 2020-10-01 16:25:00 |
| Presentation Time | 40 minutes |
| Registration for | IA |
| Paper # | IA2020-11 |
| Volume (vol) | vol.120 |
| Number (no) | no.177 |
| Page | p.31 |
| #Pages | 1 |
| Date of Issue | 2020-09-24 (IA) |
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