Pitfalls in the fluid modeling of RTT variations in window-based congestion control

Deterministic delay differential equation models, where the packet traffic is modeled as a fluid, are widely used to study congestion control algorithms in the Internet. In this paper, we point out some pitfalls in such fluid modeling of window flow control algorithms. Specifically, we argue that the modeling assumptions used to capture the variability in the RTT (due to queue length fluctuations) may play a critical role in our ability to design stable algorithms. We study two scenarios to illustrate the dramatic impact of RTT modeling. We first consider TCP-Reno with RED, and show that assuming that the RTT is a constant (when it is actually time-varying) leads to conservative parameter choices, i.e., the system continues to be stable even with variable RTT. On the other hand, for the recently proposed Stabilized Vegas, we show the following result: while the network can be stabilized under the constant RTT assumption, there is no choice of parameters that would stabilize the system when the RTT variations are taken into account! Interestingly, such problems do not arise if the congestion-control mechanisms at the end-users are rate-based.