Estimation and Control in ATM Networks

Abstract

In this paper we consider the question of how to control an ATM network in the presence of incomplete source information. Such a network must use observation and estimation to attempt to fill, at least partially, the information void if it is to achieve a reasonable degree of efficiency. We consider estimation under these assumptions. Appealing to Dynamic Programming shows that there is no theoretical evidence to support the separation of estimation and control. This is because the problem does not fit in to the celebrated framework of a linear system with quadratic cost functional. Simple arguments show that estimation and control indeed can not be separated. We also use the Bayesian approach and show that Maximum Likelihood Estimation is an unsuitable method of estimation. The fact behind all these conclusions is the extreme non-linearity of the Quality of Service as a function of the source parameters. Keywords: Dynamic Programming, ATM Networks, Bayes Estimation 1 Introduction In..