This book presents recent research on Markov chains; the articles use linear algebra and queueing models and are grouped into three sections covering theory, models, and applications. This book will highlight current issues in the area and will be useful to both pure and applied mathematicians.

Inhalt
Perturbation Theory and Error Analysis.- Error bounds for the computation of null vectors with Applications to Markov Chains.- The influence of nonnormality on matrix computations.- Componentwise error analysis for stationary iterative methods.- The character of a finite Markov chain.- Gaussian elimination, perturbation theory, and Markov chains.- Iterative Methods.- Algorithms for periodic Markov chains.- Iterative methods for queueing networks with irregular state-spaces.- Analysis of p-cyclic iterations for Markov chains.- Iterative methods for finding the stationary vector for Markov chains.- Local convergence of (exact and inexact) iterative aggregation.- Queueing Theory and Applications.- Automated generation and analysis of Markov reward models using stochastic reward nets.- Means and variances in Markov reward systems.- A direct algorithm for computing the stationary distribution of a p-cyclic Markov chain.- Approximate analysis of a discrete-time queueing model of the shared buffer ATM switch.- Algorithms for infinite Markov chains with repeating columns.- Cray-2 memory organization and interprocessor memory contention.