Predicting TCP throughput from non-invasive network sampling

In this paper, we wish to derive analytic models that predict the performance of TCP flows between specified endpoints using routinely observed network characteristics such as loss and delay. The ultimate goal of our approach is to convert network observables into representative user and application relevant performance metrics. The main contributions of this paper are in studying which network performance data sources are most reflective of session characteristics, and then in thoroughly investigating a new TCP model based on Padhye et al. (2000) that uses non-invasive network samples to predict the throughput of representative TCP flows between given end-points.