Presentation 2020-05-15
Prediction of Hyper Giants in AS topology using machine learning
Takuro Kudo, Michiko Harayama,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) For decades, the Internet penetration rate in the world is increasing rapidly. On behave of this, the structure of AS topology has been getting complicated. Our laboratory has been studied the analysis of AS topology and the index to measure the influence of Hyper Giants. In previous studies, analysis was performed focusing on the ratio of P2C connections and P2P connections for Tier1 to Tier3. From these analysis results, it would be possible to predict Hyper Giants using machine learning of the feature values of AS. In this study, we predict unknown Hyper Giants using machine learning methods based on the features of AS in the AS topology. As a result of the prediction, we could extract ASes of huge content distribution networks and of video distribution services.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) AS topology / Hyper Giants / Machine learning / Random Forest / Prediction
Paper # NS2020-14
Date of Issue 2020-05-07 (NS)

Conference Information
Committee NS
Conference Date 2020/5/14(2days)
Place (in Japanese) (See Japanese page)
Place (in English) Doshisha University
Topics (in Japanese) (See Japanese page)
Topics (in English) High level protocol, Networking technologies (IP and high-layer routing/filtering, Multicast, Quality/Routing control), IP network application technologies (P2P, P4P, Overlay, SIP, NGN), Network system related technologies (System configuration, Interface, Architecture, Hardware/Software/Middleware), Security, Blockchain etc.
Chair Yoshikatsu Okazaki(NTT)
Vice Chair Akihiro Nakao(Univ. of Tokyo)
Secretary Akihiro Nakao(Osaka Pref Univ.)
Assistant Shinya Kawano(NTT)

Paper Information
Registration To Technical Committee on Network Systems
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Prediction of Hyper Giants in AS topology using machine learning
Sub Title (in English)
Keyword(1) AS topology
Keyword(2) Hyper Giants
Keyword(3) Machine learning
Keyword(4) Random Forest
Keyword(5) Prediction
1st Author's Name Takuro Kudo
1st Author's Affiliation Gifu University Graduate School(Gifu Univ.)
2nd Author's Name Michiko Harayama
2nd Author's Affiliation Gifu University(Gifu Univ.)
Date 2020-05-15
Paper # NS2020-14
Volume (vol) vol.120
Number (no) NS-19
Page pp.pp.39-44(NS),
#Pages 6
Date of Issue 2020-05-07 (NS)