Paper Info
Title
Measuring performance of continuous-time stochastic processes using timed automata
Abstract
We propose deterministic timed automata (DTA) as a model-independent language for specifying performance and dependability measures over continuous-time stochastic processes. Technically, these measures are defined as limit frequencies of locations (control states) of a DTA that observes computations of a given stochastic process. Then, we study the properties of DTA measures over semi-Markov processes in greater detail. We show that DTA measures over semi-Markov processes are well-defined with probability one, and there are only finitely many values that can be assumed by these measures with positive probability. We also give an algorithm which approximates these values and the associated probabilities up to an arbitrarily small given precision. Thus, we obtain a general and effective framework for analysing DTA measures over semi-Markov processes.
Year
DOI
Venue
2011
10.1145/1967701.1967709
Proceedings of the 17th international conference on Hybrid systems: computation and control
Keywords
DocType
Volume
continuous-time stochastic process,associated probability,dependability measure,performance analysis,small given precision,analysing dta measure,stochastic process,timed automata,positive probability,general state space markov chains,stochastic stability,dta measure,semi-markov processes,semi-markov process,control state
Conference
abs/1101.4204
Citations 
PageRank 
References 
5
0.49
11
Authors
5
Name
Order
Citations
PageRank
Tomás Brázdil116116.23
Jan Krčál2797.45
Jan Kretínský315916.02
Antonín Kucera465855.69
Vojtĕch Řehák5365.15