Presentation 2013-04-18
A Low-Quality Link Detection Scheme Using Compressed Sensing-Based Network Tomography
Kazushi TAKEMOTO, Takahiro MATSUDA, Tetsuya TAKINE,
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Abstract(in English) Network tomography is an inference technique for internal network characteristics from end-to-end measurements. In this article, we study network tomography based on compressed sensing, which is an emerging theory in signal/image processing for acquiring sparse vectors. By applying compressed sensing to network tomography, we can efficiently detect low-quality links with the small number of measurements. We propose an online network tomography scheme for detecting links with high packet loss. In the proposed scheme, two measurement nodes establish measurement paths between them, and measure packet loss rates on these paths within every measurement window. When high packet loss rates are observed on some paths, we identify low-quality links by using compressed sensing-based network tomography. The performance of the proposed scheme is evaluated with simulation experiments.
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Keyword(in English) Network Tomography / Compressed Sensing / Sparse Vector
Paper # NS2013-1
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Committee NS
Conference Date 2013/4/11(1days)
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Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) A Low-Quality Link Detection Scheme Using Compressed Sensing-Based Network Tomography
Sub Title (in English)
Keyword(1) Network Tomography
Keyword(2) Compressed Sensing
Keyword(3) Sparse Vector
1st Author's Name Kazushi TAKEMOTO
1st Author's Affiliation Graduate School of Engineering, Osaka University()
2nd Author's Name Takahiro MATSUDA
2nd Author's Affiliation Graduate School of Engineering, Osaka University
3rd Author's Name Tetsuya TAKINE
3rd Author's Affiliation Graduate School of Engineering, Osaka University
Date 2013-04-18
Paper # NS2013-1
Volume (vol) vol.113
Number (no) 4
Page pp.pp.-
#Pages 6
Date of Issue