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CALINESCU, R. ČEŠKA, M. GERASIMOU, S. KWIATKOWSKA, M. PAOLETTI, N.
Originální název
Efficient Synthesis of Robust Models for Stochastic Systems
Typ
článek v časopise ve Web of Science, Jimp
Jazyk
angličtina
Originální abstrakt
We describe a tool-supported method for the efficient synthesis of parametric continuous-time Markov chains (pCTMC) that correspond to robust designs of a system under development. The pCTMCs generated by our RObust DEsign Synthesis (RODES) method are resilient to changes in the systems operational profile, satisfy strict reliability, performance and other quality constraints, and are Pareto-optimal or nearly Pareto-optimal with respect to a set of quality optimisation criteria. By integrating sensitivity analysis at designer-specified tolerance levels and Pareto optimality, RODES produces designs that are potentially slightly suboptimal in return for less sensitivity-an acceptable trade-off in engineering practice. We demonstrate the effectiveness of our method and the efficiency of its GPU-accelerated tool support across multiple application domains by using RODES to design a producer-consumer system, a replicated file system and a workstation cluster system.
Klíčová slova
Software performance and reliability engineering, Probabilistic model synthesis, Multi-objective optimisation, Robust design
Autoři
CALINESCU, R.; ČEŠKA, M.; GERASIMOU, S.; KWIATKOWSKA, M.; PAOLETTI, N.
Vydáno
9. 5. 2018
Nakladatel
ELSEVIER SCIENCE INC
Místo
NEW YORK
ISSN
0164-1212
Periodikum
JOURNAL OF SYSTEMS AND SOFTWARE
Ročník
2018
Číslo
143
Stát
Spojené státy americké
Strany od
140
Strany do
158
Strany počet
18
URL
https://doi.org/10.1016/j.jss.2018.05.013
BibTex
@article{BUT155049, author="Radu {Calinescu} and Milan {Češka} and Simos {Gerasimou} and Marta {Kwiatkowska} and Nicola {Paoletti}", title="Efficient Synthesis of Robust Models for Stochastic Systems", journal="JOURNAL OF SYSTEMS AND SOFTWARE", year="2018", volume="2018", number="143", pages="140--158", doi="10.1016/j.jss.2018.05.013", issn="0164-1212", url="https://doi.org/10.1016/j.jss.2018.05.013" }