A heuristic procedure for compact Markov representation of PH distributions

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 compari...

Full description

Bibliographic Details
Main Authors: Illes Horvath, Miklos Telek
Format: Article
Language:English
Published: European Alliance for Innovation (EAI) 2015-12-01
Series:EAI Endorsed Transactions on Internet of Things
Subjects:
Online Access:https://eudl.eu/pdf/10.4108/icst.valuetools.2014.258174
id doaj-9c660efb73d84ea08d43e1904be7c84b
record_format Article
spelling doaj-9c660efb73d84ea08d43e1904be7c84b2020-11-25T01:37:52ZengEuropean Alliance for Innovation (EAI)EAI Endorsed Transactions on Internet of Things2414-13992015-12-011410.4108/icst.valuetools.2014.258174A heuristic procedure for compact Markov representation of PH distributionsIlles Horvath0Miklos Telek1MTA-BME Information Systems Research GroupDepartment of Networked Systems and Services Budapest University of Technology and EconomicsThe 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.https://eudl.eu/pdf/10.4108/icst.valuetools.2014.258174ph distributionminimal representationfeedback erlang blockunicyclic block
collection DOAJ
language English
format Article
sources DOAJ
author Illes Horvath
Miklos Telek
spellingShingle Illes Horvath
Miklos Telek
A heuristic procedure for compact Markov representation of PH distributions
EAI Endorsed Transactions on Internet of Things
ph distribution
minimal representation
feedback erlang block
unicyclic block
author_facet Illes Horvath
Miklos Telek
author_sort Illes Horvath
title A heuristic procedure for compact Markov representation of PH distributions
title_short A heuristic procedure for compact Markov representation of PH distributions
title_full A heuristic procedure for compact Markov representation of PH distributions
title_fullStr A heuristic procedure for compact Markov representation of PH distributions
title_full_unstemmed A heuristic procedure for compact Markov representation of PH distributions
title_sort heuristic procedure for compact markov representation of ph distributions
publisher European Alliance for Innovation (EAI)
series EAI Endorsed Transactions on Internet of Things
issn 2414-1399
publishDate 2015-12-01
description 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.
topic ph distribution
minimal representation
feedback erlang block
unicyclic block
url https://eudl.eu/pdf/10.4108/icst.valuetools.2014.258174
work_keys_str_mv AT illeshorvath aheuristicprocedureforcompactmarkovrepresentationofphdistributions
AT miklostelek aheuristicprocedureforcompactmarkovrepresentationofphdistributions
AT illeshorvath heuristicprocedureforcompactmarkovrepresentationofphdistributions
AT miklostelek heuristicprocedureforcompactmarkovrepresentationofphdistributions
_version_ 1725056797074522112