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CALINESCU, R. ČEŠKA, M. GERASIMOU, S. KWIATKOWSKA, M. PAOLETTI, N.
Original Title
Efficient Synthesis of Robust Models for Stochastic Systems
Type
journal article in Web of Science
Language
English
Original Abstract
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.
Keywords
Software performance and reliability engineering, Probabilistic model synthesis, Multi-objective optimisation, Robust design
Authors
CALINESCU, R.; ČEŠKA, M.; GERASIMOU, S.; KWIATKOWSKA, M.; PAOLETTI, N.
Released
9. 5. 2018
Publisher
ELSEVIER SCIENCE INC
Location
NEW YORK
ISBN
0164-1212
Periodical
JOURNAL OF SYSTEMS AND SOFTWARE
Year of study
2018
Number
143
State
United States of America
Pages from
140
Pages to
158
Pages count
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" }