Self-optimizing window flow control in high-speed data networks

Abstract

The critical parameter in a window flow control scheme is the window size, which represents the maximum number of packets that can be in transit at a time. In this paper, we consider the problem of selecting the optimum window size in high-speed data networks. A self-optimizing method is proposed to adapt the window size to network conditions. The scheme employs a cross-correlation technique for process identification where the perturbation signal is random. Simulation results are presented for the isarithmic flow control to show the convergence rate and stability characteristics of the self-optimizing scheme.