Evaluating and modeling window synchronization in highly multiplexed flows

In this paper, we investigate issues of synchronization in highly aggregated flows such as would be found in the Internet backbone. Our hypothesis is that regularly spaced loss events lead to window synchronization in long lived flows. We argue that window synchronization is likely to be more common in the Internet than previously reported. We support our argument with evidence of the existence and evaluation of the characteristics of periodic discrete congestion events using active probe data gathered in the Surveyor infrastructure. When connections experience loss events which are periodic, the aggregate offered load to neighboring links rises and falls in cadence with the loss events. Connections whose cWnd values grow from W/2 to W at approximately the same rate as the loss event period soon synchronize their cWnd additive increases and multiplicative decreases. We find that this window synchronization can scale to large numbers of connections depending on the diversity of roundtrip times of individual flows. A model is presented that predicts important characteristics of the loss events in window synchronized flows including the quantity, intensity, and duration. The model effectively explains the prevalence of discrete loss events in fast links with high multiplexing factors as well as the queue buildup and queue draining phases of congestion.