An adaptive framework for dynamic access to bandwith at high speeds

Abstract

Emerging technologies for high-speed data network provide users with explicit feedback about congestion. Users, however, have questioned whether feedback can help in avoiding congestion in wide-area networks that operate at speeds of multiple megabits- or gigabits-per-second. In this paper we analyze a class of adaptive schemes with delayed feedback, where adaptive sources interact with each other as well as with non-adaptive sources through a single queue. We model the network as a stochastic, delay-differential equation and the rate at which an adaptive source transmits data as a fluid. Our model accounts for different levels of traffic burstiness introduced by the non-adaptive sources and for distinct propagation delays for different adaptive sources. We show how the performance of the system scales with increasing network speeds for quite general fluctuations in the bandwidth available to the adaptive sources. Simulation results show the accuracy of the model's predictions as a function of key parameters. This paper should raise the expectations of users about the potential effectiveness of responding to congestion notification.