Performance analysis of AIMD mechanisms over a multi-state Markovian path

We analyze the performance of an Additive Increase Multiplicative Decrease (AIMD)-like flow control mechanism. The transmission rate is considered to increase linearly in time until the receipt of a congestion notification, when the transmission rate is multiplicatively decreased. AIMD captures the steady state behavior of TCP in the absence of timeouts and in the absence of maximum window size limitation. We introduce a general fluid model based on a multi-state Markov chain for the moments at which the congestion is detected. With this model, we are able to account for correlation and burstiness in congestion moments. Furthermore, we specify several simple versions of our general model and then we identify their parameters from real TCP traces.