Randomization for Markov chains with applications to networks in a random environment

Abstract: We develop randomized modifications of Markov chains and apply these modifications to the routing chains of customers in Jacksonian stochastic networks. The aim of our investigations is to find new rerouting schemes for non standard Jackson networks which hitherto resist computing explicitly the stationary distribution. The non standard properties we can handle by suitable algorithms encompass several modifications of Jackson networks known in the literature, especially breakdown and repair of nodes with access modification for customers to down nodes, finite buffers with control of buffer overflow. The rerouting schemes available in the literature for these situations are special cases of our rerouting schemes, which can deal also with partial degrading of service capacities and even with speed up of service. In any case we require our algorithms to react on such general changes in the network with the aim to maintain the utilization of the nodes. To hold this invariant under change of service speeds (intensities) our algorithms not only adapt the routing probabilities but decrease automatically the overall arrival rate to the network if necessary. Our main application is for stochastic networks in a random environment. The impact of the environment on the network is by changing service speeds (by upgrading and/or degrading, breakdown, repair) and we implement the randomization algorithms to react to the changes of the environment. On the other side, customers departing from the network may enforce the environment to jump immediately. So our environment is not Markov for its own. The main result is to compute explicitly the joint stationary distribution of the queue lengths vector and the environment which is of product form: Environment and queue lengths vector, and the queue lengths over the network are decomposable.