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 ...

We present a combinatorial framework for the study of a natural class of distributed optimization problems that involve decisionmaking by a collection of n distributed agents in the presence of incomplete information