Skip to Main Content
To develop an accurate parametric model for network characteristics is very difficult. We propose a fitting-based adaptive sampling methodology (FASM) trying to model some network metrics non-parametrically. The contributions of the paper are twofold: (1) adopting a piecewise linear function approximation scheme to provide more accurate approximation of the true metric model; (2) the statistical metric derived from the non-parametric model provides much more stable, lower variance and accurate estimation than other popular methodologies under the same sampling size. Experiments based on two measurement traces show that FASM dramatically reduces the number of samples while retaining the same approximating residual error than other methods.