Section: New Results

Perfect simulation

We have proposed a new approach for sampling the stationary distribution of general Markov chains that only needs to consider two trajectories. We show that this new approach is particularly effective when the state space can be partitioned into pieces where envelopes can be easily computed [26] . We further show that most Markovian queuing networks have this property and we propose efficient algorithms for some of them, in particular when the rates of events range over several orders of magnitude [45] . We also provided a novel approach for efficient sampling of queues with phase type servers [37] (this paper has received the best paper award at ASMTA 2011) and Markov chains with infinite state spaces (but with a known bounding process). Perfect sampling has been used for model checking of probabilistic models in [14] .