Routing algorithms and stochastic analysis for large communications networks

As part of our ONR sponsored research in the subtopic Linear-Time Stochastic Algorithms, we began investigating an optimization technique known as simulated annealing. We have succeeded in giving a necessary and sufficient condition for the annealing algorithms to converge. New algorithms have been developed for open-loop computation of optimal state-dependent routine strategies for a fluid-approximation communication network model with a single destination. One of the algorithms is an efficient combinatorial algorithm based on the solution of max-flow problems for networks the same size as the original network. A new theory of distributed resource allocation was proposed. The work addresses problems of route selection and scheduling in communication networks. In a large distributed communication network, the decisions that individual stations can make should sometimes be purposely limited a priori in order to facilitate the coordination of such decisions. Such limitations might be placed at one layer of protocol by mechanisms operating at a higher protocol level.