An Adaptive Sampling Methodology for Internet Traffic Data Measurement

Current popular sampling algorithms canpsilat provide accurate approximation of true character under the circumstance of network traffic bursting. In the paper, we develop an adaptive network traffic sampling methodology (MANFC-AT) based on aggregated time-serial evolution trend. The MANFC-AT algorithm adaptively adjusts the time interval between consecutive samples according to the evolution trend of network traffic which is estimated from the obtained samples. Then it is able to approximate the measured traffic more precisely. Compared with current popular sampling algorithms, MANFC-AT algorithm can provide more precise estimation of network traffic, only requires fewer samples,contains more information about network traffic bursting.