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  4. Network Loss Inference with Second Order Statistics of End-to-End Flows
 
conference paper

Network Loss Inference with Second Order Statistics of End-to-End Flows

Nguyen, Hung X.
•
Thiran, Patrick  
2007
ACM Internet Measurement Conference (IMC'07)
ACM Internet Measurement Conference (IMC'07)

We address the problem of calculating link loss rates from end-to-end measurements. Contrary to existing works that use only the average end-to-end loss rates or strict temporal correlations between probes, we exploit second-order moments of end-to-end flows. We first prove that the variances of link loss rates can be uniquely calculated from the covariances of the measured end-to-end loss rates in any realistic topology. After calculating the link variances, we remove the un-congested links with small variances from the first-order moment equations to obtain a full rank linear system of equations, from which we can calculate precisely the loss rates of the remaining congested links. This operation is possible because losses due to congestion occur in bursts and hence the loss rates of congested links have high variances. On the contrary, most links on the Internet are un-congested, and hence the averages and variances of their loss rates are virtually zero. Our proposed solution uses only regular unicast probes and thus is applicable in today's Internet. It is accurate and scalable, as shown in our simulations and experiments on PlanetLab.

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Type
conference paper
DOI
10.1145/1298306.1298339
Web of Science ID

WOS:000266204100025

Author(s)
Nguyen, Hung X.
Thiran, Patrick  
Date Issued

2007

Published in
ACM Internet Measurement Conference (IMC'07)
Start page

227

End page

240

Subjects

Network Tomography

•

Identifiability

•

Inference

URL

URL

http://conferences.sigcomm.org/imc/2007/
Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LCA  
INDY2  
Event nameEvent placeEvent date
ACM Internet Measurement Conference (IMC'07)

San Diego, USA

October 24-26, 2007

Available on Infoscience
August 23, 2007
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/10419
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