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Paper Abstract and Keywords
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
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.
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 Print edition: ISSN 0913-5685  Online edition: ISSN 2432-6380
Copyright
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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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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
Date of Issue 2020-09-24 (IA) 


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