Probabilistic Evaluation for the Analytical Solution of Large Markov Models: Algorithms and Tool Support

Probabilistic Evaluation for the Analytical Solution of Large Markov Models: Algorithms and Tool Support (1995)

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by Aad P. A. Van Moorsel , Boudewijn R. Haverkort , Rheinisch-westfalische Technische , Hochschule Aachen

Venue:	Microelectronics and Reliability
Citations:	9 - 4 self

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Datum	Value	Source
TITLE	Probabilistic Evaluation for the Analytical Solution of Large Markov Models: Algorithms and Tool Support	user correction - Legacy Corrections
AUTHOR NAME	Aad P. A. Van Moorsel	SVM HeaderParse 0.1
AUTHOR AFFIL	University of Illinois at Urbana-Champaign; Center for Reliable and High-Performance Computing	SVM HeaderParse 0.2
AUTHOR ADDR	1308 W. Main St. Urbana, IL 61801-228	SVM HeaderParse 0.1
AUTHOR NAME	Boudewijn R. Haverkort	SVM HeaderParse 0.1
AUTHOR AFFIL	LFG Informatik IV---Distributed Systems	SVM HeaderParse 0.2
AUTHOR ADDR	Ahornstrasse 55, D-52056 Aachen, Germany	SVM HeaderParse 0.1
AUTHOR NAME	Rheinisch-westfalische Technische	SVM HeaderParse 0.1
AUTHOR AFFIL	LFG Informatik IV---Distributed Systems	SVM HeaderParse 0.2
AUTHOR ADDR	Ahornstrasse 55, D-52056 Aachen, Germany	SVM HeaderParse 0.1
AUTHOR NAME	Hochschule Aachen	SVM HeaderParse 0.1
AUTHOR AFFIL	LFG Informatik IV---Distributed Systems	SVM HeaderParse 0.2
AUTHOR ADDR	Ahornstrasse 55, D-52056 Aachen, Germany	SVM HeaderParse 0.1
ABSTRACT	Over the past decade constantly increasing computer power has made analytic solution of Markovian performance and dependability models more attractive. However, its application for practical systems still needs improvement since detailed and realistic models typically result in Markov (reward) models that are too large to completely generate and store in memory. In this paper we discuss this problem of largeness of Markov reward models and propose solutions if transient measures are considered. We will introduce a novel approach, called probabilistic evaluation, based on the probabilistic verification and validation methods known in the area of communication protocol analysis. In order to apply these ideas to solve for transient reward measures, we develop algorithms that do not rely on a priori generation of the whole state space. Instead, only parts of the state space will be considered at a time, and states that are not needed to get accurate results will not be generated. We will n...	user correction - Legacy Corrections
YEAR	1995	user correction - Legacy Corrections
VENUE	Microelectronics and Reliability	INFERENCE
VENUE TYPE	JOURNAL	INFERENCE
PAGES	733--755	INFERENCE
VOLUME	36	INFERENCE
CITATIONS	22 found	ParsCit 1.0