Optimization of resource control in communication systems

We consider a class of resource control problems in communication systems, such as packet-switched networks and telephone networks, which consist of spatially distributed resources and multiple controllers. In the problems we examine, small units of work (messages, telephone calls) arrive randomly in large numbers to the system, utilize some resources and then leave. In controlling system parameters on-line for the optimal usage of these resources, it is often prohibitively expensive to pass around instantaneous state information to the controllers in order to facilitate dynamic scheduling and thus, what is desirable is optimization with respect to some long term statistics of the random system behavior. We study the case in which little is assumed about the effects of the control parameters on the networks\u27 performance. In this case on-line measurements (prone to random errors or noise) can still be taken and used to help improve performance. A general technique for using such error-prone measurements to iteratively improve system performance, called stochastic approximation, has been advanced since the 50\u27s and studied extensively. We study the use of resource allocation algorithms based on stochastic approximation, present a new stochastic approximation technique and demonstrate its use in a class of chosen problems. The new technique is shown to have several advantages, including the ability to handle estimator bias, which is prevalent in several known estimators. Both theoretical and experimental results have been obtained, including the case of multiple, asynchronously operating controllers and where control parameter constraints are unknown and must themselves be estimated