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CSE
2009
IEEE

Self-Tuning the Parameter of Adaptive Non-linear Sampling Method for Flow Statistics

10 years 2 months ago
Self-Tuning the Parameter of Adaptive Non-linear Sampling Method for Flow Statistics
—Flow statistics is a basic task of passive measurement and has been widely used to characterize the state of the network. Adaptive Non-Linear Sampling (ANLS)is one of the most accurate and memory-efficient flow statistics method proposed recently. This paper studies the parameter setting problem for ANLS. A parameter self-tuning algorithm is proposed in this paper, which enlarges the parameter to a equilibrium tuning point and renormalizes the counter when counter overflows. It is demonstrated that the estimation error of ANLS with parameter self-tuning algorithm is improved by about 89 times for real trace, 70 times for Pareto traffic scenario and 370 times for exponential traffic, while giving the same memory size.
Chengchen Hu, Bin Liu
Added 20 May 2010
Updated 20 May 2010
Type Conference
Year 2009
Where CSE
Authors Chengchen Hu, Bin Liu
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