IoT 15(4): e2

Research Article

A heuristic procedure for compact Markov representation of PH distributions

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  • @ARTICLE{10.4108/icst.valuetools.2014.258174,
    author={Illes Horvath and Miklos Telek},
    title={A heuristic procedure for compact Markov representation of PH distributions},
    journal={EAI Endorsed Transactions on Internet of Things},
    volume={1},
    number={4},
    publisher={EAI},
    journal_a={IOT},
    year={2015},
    month={2},
    keywords={ph distribution, minimal representation, feedback erlang block, unicyclic block},
    doi={10.4108/icst.valuetools.2014.258174}
}
  • Illes Horvath
    Miklos Telek
    Year: 2015
    A heuristic procedure for compact Markov representation of PH distributions
    IOT
    EAI
    DOI: 10.4108/icst.valuetools.2014.258174
Illes Horvath1,*, Miklos Telek2
  • 1: MTA-BME Information Systems Research Group
  • 2: Department of Networked Systems and Services Budapest University of Technology and Economics
*Contact email: horvath.illes.antal@gmail.com

Abstract

The minimal Markovian representation of PH distributions is an open research problem, which was actively investigated during the last two decades. We present a numerical method for finding small Markovian representation of PH distributions and investigate the general quality of the method by comparing the size of the obtained representation with the size of the representation obtained by alternative methods. Our numerical method intends to find a small Markovian representation. We report examples when the obtained representation is larger than the minimal Markovian representation.

Keywords
ph distribution, minimal representation, feedback erlang block, unicyclic block
Published
19th Feb 2015
Publisher
EAI
http://dx.doi.org/10.4108/icst.valuetools.2014.258174

Copyright © 2015 I. Horvath and M. Telek, licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.