Modelling and analysis of TCP congestion control mechanisms using stochastic reward nets

Abstract

Modelling of congestion control mechanisms of the transmission control protocol (TCP) helps to obtain parametric results that help to better understand the TCP behaviour under different operating conditions. Several analytical models were proposed to analyse the behaviour of TCP congestion control mechanisms. However, most of these models were designed for a few TCP sessions with non-persistent connections. A few analytical studies were presented for modelling persistent TCP connections. Nevertheless, these studies have many limiting assumptions and are not scalable. In this work, a stochastic reward nets model is introduced for the TCP Reno with the persistent TCP connections, which share two bottleneck links in a wide area network. A microscopic approach was used for constructing the proposed model that captures most features of congestion control mechanisms used by the TCP Reno, and interactions between different TCP sessions. The proposed model relaxed several limiting assumptions adopted by other related models introduced in the literature. To validate the proposed model, analytical results are extensively compared with simulation results.