Mean-Payoff Optimization in Continuous-Time Markov Chains with Parametric Alarms

Publikation: Beitrag in Buch/Konferenzbericht/Sammelband/GutachtenBeitrag in KonferenzbandBeigetragen

Beitragende

Abstract

Continuous-time Markov chains with alarms (ACTMCs) allow for alarm events that can be non-exponentially distributed. Within parametric ACTMCs, the parameters of alarm-event distributions are not given explicitly and can be subject of parameter synthesis. An algorithm solving the ε-optimal parameter synthesis problem for parametric ACTMCs with long-run average optimization objectives is presented. Our approach is based on reduction of the problem to finding long-run average optimal strategies in semi-Markov decision processes (semi-MDPs) and sufficient discretization of parameter (i.e., action) space. Since the set of actions in the discretized semi-MDP can be very large, a straightforward approach based on explicit action-space construction fails to solve even simple instances of the problem. The presented algorithm uses an enhanced policy iteration on symbolic representations of the action space. The soundness of the algorithm is established for parametric ACTMCs with alarm-event distributions satisfying four mild assumptions that are shown to hold for uniform, Dirac, exponential, and Weibull distributions in particular, but are satisfied for many other distributions as well. An experimental implementation shows that the symbolic technique substantially improves the efficiency of the synthesis algorithm and allows to solve instances of realistic size.

Details

OriginalspracheEnglisch
TitelQuantitative Evaluation of Systems
Herausgeber (Verlag)Springer, Berlin [u. a.]
Seiten190-206
Seitenumfang17
ISBN (Print)978-3-319-66334-0
PublikationsstatusVeröffentlicht - 2017
Peer-Review-StatusNein

Publikationsreihe

ReiheLecture Notes in Computer Science, Volume 10503
ISSN0302-9743

Konferenz

Titel14th International Conference of Quantitative Evaluation of SysTems
KurztitelQEST 2017
Veranstaltungsnummer14
BeschreibungCo-located with the 28th International Conference on Concurrency Theory (CONCUR 2017) and the 14th European Performance Engineering Workshop (EPEW 2017)
Dauer5 - 7 September 2017
Webseite
BekanntheitsgradInternationale Veranstaltung
OrtHarnack-Haus
StadtBerlin
LandDeutschland

Externe IDs

Scopus 85028645372
ORCID /0000-0002-5321-9343/work/142236700

Schlagworte

Schlagwörter

  • Mean-Payoff Optimization, Continuous-Time Markov Chains, Parametric Alarms