Analytical modeling of Transmission Control Protocol NewReno using Generalized Stochastic Petri Nets

This paper presents a novel analytical model of Transmission Control Protocol (TCP) using a generalized stochastic Petri net (GSPN). Extensive simulation work has been done for the performance evaluation of TCP NewReno protocol. In view of the limitations of the simulation technique, we present an analytical approach using GSPN. A GSPN is a useful mathematical tool that solves continuous time Markov chains for complex systems and evaluates the stationary behavior. In this paper, we analyze the slow-but-steady variant of TCP NewReno. The model captures the behavioral aspects of the slow start and the congestion avoidance phase together with the fast retransmit and recovery capabilities of TCP NewReno. Performance metrics such as throughput, goodput, and task completion time of the system are obtained. The effect of variation in the model parameters on the performance is studied. The results are validated using the network simulator, and their accuracy is verified by evaluating the confidence interval. The performance of the proposed model is compared with that of TCP Reno. The performance of the proposed model is also compared with one of the previous models. The numerical illustrations and comparison of the proposed technique with simulation validates the accuracy, efficiency, and competence of the GSPN technique. While GSPN modeling for TCP is investigated in depth for the TCP NewReno and TCP Reno variant in this paper, other protocols could be also analyzed similarly. Copyright (c) 2013 John Wiley & Sons, Ltd.