摘要
Packet-pair sampling, also called probe gap model (PGM) is proposed as a lightweight and fast available bandwidth measurement method. But measurement tools based on PGM gives results with great uncertainty in some cases. PGM’s statistical robustness has not been proved. In this paper we propose a more precise statistical model based on PGM. We present the new approach by using probability distribution and statistical parameters. We also investigate the use of a PGM bandwidth evaluation method considering a non-fluid cross traffic and present the alternative approach where the bursty nature of the probed traffic could be taken into account. Based on the model, measurement variance and sample size can be calculated to improve the measurement accuracy. We evaluated the model in a controlled and reproducible environment using NS simulations.
Packet-pair sampling, also called probe gap model (PGM) is proposed as a lightweight and fast available bandwidth measurement method. But measurement tools based on PGM gives results with great uncertainty in some cases. PGM’s statistical robustness has not been proved. In this paper we propose a more precise statistical model based on PGM. We present the new approach by using probability distribution and statistical parameters. We also investigate the use of a PGM bandwidth evaluation method considering a non-fluid cross traffic and present the alternative approach where the bursty nature of the probed traffic could be taken into account. Based on the model, measurement variance and sample size can be calculated to improve the measurement accuracy. We evaluated the model in a controlled and reproducible environment using NS simulations.
