Efficient Synthesis of Robust Models for Stochastic Systems

Radu Constantin Calinescu; Milan Ceska; Simos Gerasimou; Marta Kwiatkowska; Nicola Paoletti

doi:10.1016/j.jss.2018.05.013

Efficient Synthesis of Robust Models for Stochastic Systems

Radu Constantin Calinescu, Milan Ceska, Simos Gerasimou, Marta Kwiatkowska, Nicola Paoletti

Computer Science

Research output: Contribution to journal › Article › peer-review

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 system’s 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.

Original language	English
Pages (from-to)	140-158
Number of pages	19
Journal	Journal of Systems and Software
Volume	143
Early online date	16 May 2018
DOIs	https://doi.org/10.1016/j.jss.2018.05.013
Publication status	Published - Sept 2018

Bibliographical note

Keywords

software performance and reliability engineering
robust design
probabilistic model synthesis
multi-objective optimisation
Probabilistic model synthesis
Software performance and reliability engineering
Robust design
Multi-objective optimisation

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10.1016/j.jss.2018.05.013

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title = "Efficient Synthesis of Robust Models for Stochastic Systems",

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 system{\textquoteright}s 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.",

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AU - Calinescu, Radu Constantin

AU - Ceska, Milan

AU - Gerasimou, Simos

AU - Kwiatkowska, Marta

AU - Paoletti, Nicola

PY - 2018/9

Y1 - 2018/9

N2 - 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 system’s 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.

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KW - multi-objective optimisation

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KW - Multi-objective optimisation

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Efficient Synthesis of Robust Models for Stochastic Systems

Abstract

Bibliographical note

Keywords

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Simos Gerasimou

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