Optimal rate control for high speed telecommunication networks

We present in this paper two approaches for designing controllers that dynamically regulate the rate of data flow into a network based on feedback state information. They result in controllers that are similar to ones that have been advocated for both end-to-end and hop-by-hop congestion control in high-speed networks. Many existing control protocols have been developed on growing available experience, using ad-hoc techniques that did not come as a result of a control-theoretical study. This is due to the high complexity of the controlled systems, that are typically decentralized, have non-linear dynamics, and may only use partial noisy delayed information. Some attempts have been made in recent years to use control theory to design flow controllers with, however, no explicit objective functions to be minimized; moreover, the class of control policies in existing theoretical work is quite restricted. In this paper we formulate explicitly some cost criteria to be minimized, related to performance measures such as delays, throughputs and loss probabilities. Using a linearized model, we then view the design problem as an optimal control problem. We follow two approaches to model interfering traffic and other unknown data: the H^∞ approach, and the LQG one; and determine for both cases the optimal controllers. Some simulation results complete the study.