A Markovian Approximation of TCP Compound
Sudheer Poojary, Vinod Pravin Sharma · arXiv (Cornell University) · 2015
In this paper, we derive expressions for throughput of TCP Compound connections under random losses. Throughput expressions for TCP Compound under a deterministic loss model exist in the literature. These are obtained assuming the window sizes are continuous, i.e., a fluid behaviour is assumed. We validate this model theoretically. We show that under the deterministic loss model, the TCP window evolution for TCP Compound is periodic and is independent of the initial window size. We then consider the case when packets are lost independently of each other randomly. We discuss Markov chain models to analyze performance of TCP in this scenario. Specifically, we consider appropriately scaled window size processes, indexed by p (the packet error rate). We show that these processes, converge to a limit Markov chain process as p goes to 0. We show the existence and uniqueness of the stationary distribution for this limit process. Using the stationary distribution for the limit process, we obtain approximations for throughput, under random losses, for TCP Compound when packet error rates are small. We compare our results with ns2 simulations which show a good match.