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International Parallel and Distributed Processing Symposium (IPDPS'03)
Distributed Computation of Passage Time Quantiles and Transient State Distributions in Large Semi-Markov Models
Nice, France
April 22-April 26
ISBN: 0-7695-1926-1
ASCII Text
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Jeremy T. Bradley, Nicholas J. Dingle, Peter G. Harrison, William J. Knottenbelt, "Distributed Computation of Passage Time Quantiles and Transient State Distributions in Large Semi-Markov Models," Parallel and Distributed Processing Symposium, International, pp. 281a, International Parallel and Distributed Processing Symposium (IPDPS'03), 2003.
 
 
BibTex
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@article{ 10.1109/IPDPS.2003.1213505,
author = {Jeremy T. Bradley and Nicholas J. Dingle and Peter G. Harrison and William J. Knottenbelt},
title = {Distributed Computation of Passage Time Quantiles and Transient State Distributions in Large Semi-Markov Models},
journal ={Parallel and Distributed Processing Symposium, International},
volume = {0},
year = {2003},
issn = {1530-2075},
pages = {281a},
doi = {http://doi.ieeecomputersociety.org/10.1109/IPDPS.2003.1213505},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
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TY - CONF
JO - Parallel and Distributed Processing Symposium, International
TI - Distributed Computation of Passage Time Quantiles and Transient State Distributions in Large Semi-Markov Models
SN - 1530-2075
SP
EP
A1 - Jeremy T. Bradley,
A1 - Nicholas J. Dingle,
A1 - Peter G. Harrison,
A1 - William J. Knottenbelt,
PY - 2003
KW - null
VL - 0
JA - Parallel and Distributed Processing Symposium, International
ER -
 
Jeremy T. Bradley, Imperial College of Science, Technology and Medicine
Nicholas J. Dingle, Imperial College of Science, Technology and Medicine
Peter G. Harrison, Imperial College of Science, Technology and Medicine
William J. Knottenbelt, Imperial College of Science, Technology and Medicine
Semi-Markov processes (SMPs) are expressive tools for modelling concurrent systems; they are a generalisation of Markov processes that allow for arbitrarily distributed sojourn times. This paper presents an iterative technique for passage time and transient analysis of large structurally unrestricted semi-Markov processes. Our method is based on the calculation and subsequent numerical inversion of Laplace transforms and is amenable to a highly scalable distributed implementation. Results for a distributed voting system model with up to 1.1 million states are presented and compared against simulation.
Citation:
Jeremy T. Bradley, Nicholas J. Dingle, Peter G. Harrison, William J. Knottenbelt, "Distributed Computation of Passage Time Quantiles and Transient State Distributions in Large Semi-Markov Models," ipdps, pp.281a, International Parallel and Distributed Processing Symposium (IPDPS'03), 2003
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