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Author Harrison, Peter G. ♦ Knottenbelt, William J.
Source ACM Digital Library
Content type Text
Publisher Association for Computing Machinery (ACM)
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Abstract Probability distributions of response times are important in the design and analysis of transaction processing systems and computer-communication 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 results for semi-Markov chains are also presented.
Description Affiliation: Imperial College of Science, Technology and Medicine, London SW7 2BZ, United Kingdom (Harrison, Peter G.; Knottenbelt, William J.)
Age Range 18 to 22 years ♦ above 22 year
Educational Use Research
Education Level UG and PG
Learning Resource Type Article
Publisher Date 2014-01-10
Publisher Place New York
Journal ACM SIGMETRICS Performance Evaluation Review (PERV)
Volume Number 30
Issue Number 1
Page Count 9
Starting Page 77
Ending Page 85

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Source: ACM Digital Library