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SIGMETRICS
2002
ACM

Passage time distributions in large Markov chains

13 years 10 months ago
Passage time distributions in large Markov chains
Probability distributions of response times are important in the design and analysis of transaction processing systems and computercommunication systems. We present a general technique for deriving such distributions from high-level modelling formalisms whose state spaces can be mapped onto finite Markov chains. We use a load-balanced, distributed implementation to find the Laplace transform of the first passage time density and its derivatives at arbitrary values of the transform parameter s. Setting s = 0 yields moments while the full passage time distribution is obtained using a novel distributed Laplace transform inverter based on the Laguerre method. We validate our method against a variety of simple densities, cycle time densities in certain overtake-free (tree-like) queueing networks and a simulated Petri net model. Our implementation is thereby rigorously validated and has already been applied to substantial Markov chains with over 1 million states. Corresponding theoretical r...
Peter G. Harrison, William J. Knottenbelt
Added 23 Dec 2010
Updated 23 Dec 2010
Type Journal
Year 2002
Where SIGMETRICS
Authors Peter G. Harrison, William J. Knottenbelt
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