DocumentCode :
1913707
Title :
On Passive One-Way Loss Measurements Using Sampled Flow Statistics
Author :
Gu, Yu ; Breslau, Lee ; Duffield, Nick ; Sen, Subhabrata
Author_Institution :
NEC Labs., Princeton, NJ
fYear :
2009
fDate :
19-25 April 2009
Firstpage :
2946
Lastpage :
2950
Abstract :
The ability to scalably measure one-way packet loss across different network paths is vital to IP network management. However, the effectiveness of active-measurement techniques depends on being able to deploy measurement hosts at appropriate locations, and to inject necessary amounts of probe traffic without impacting the performance of interest. On the other hand, existing passive-measurement methods like [1] require router support and suffer from deployment limitations for the foreseeable future. In this paper, we propose a new estimation technique that does not require any new router features or measurement infrastructure, and only uses the sampled flow level statistics that are routinely collected in operational networks. The technique is designed to handle challenges of sampled flow-level aggregation such as information aggregation and non-alignment of flow records with measurement intervals. We develop three different schemes and derive analytical bounds on the variance of loss estimation from such a flow-based approach. Our analysis shows that link data rates are now becoming sufficiently large to counteract the effects on sampling on estimation accuracy.
Keywords :
IP networks; computer network management; statistical analysis; telecommunication network routing; telecommunication traffic; IP network management; active-measurement technique; network router; network traffic; one-way packet loss measurement; sampled flow level statistics; Distortion measurement; Fluid flow measurement; IP networks; Loss measurement; Monitoring; Performance loss; Probes; Sampling methods; Statistics; Telecommunication traffic;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
INFOCOM 2009, IEEE
Conference_Location :
Rio de Janeiro
ISSN :
0743-166X
Print_ISBN :
978-1-4244-3512-8
Electronic_ISBN :
0743-166X
Type :
conf
DOI :
10.1109/INFCOM.2009.5062264
Filename :
5062264
Link To Document :
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