Efficiency of oblivious versus non-oblivious schedulers for optimistic, rate-based flow control

Abstract

Lower and upper bounds on convergence complexity, under varying degrees of locality, for optimistic, rate-based flow control algorithms are established. It is shown that randomness can be exploited to yield an even simpler oblivious algorithm at the price of a small increase in convergence complexity. The results for partially oblivious algorithms imply that knowledge of session rates cannot merely suffice to reduce convergence complexity.