Efficient synthesis of robust models for stochastic systems

被引:44
作者
Calinescu, Radu [1 ]
Ceska, Milan [2 ]
Gerasimou, Simos [1 ]
Kwiatkowska, Marta [3 ]
Paoletti, Nicola [4 ]
机构
[1] Univ York, Dept Comp Sci, York, N Yorkshire, England
[2] Brno Univ Technol, Fac Informat Technol, Brno, Czech Republic
[3] Univ Oxford, Dept Comp Sci, Oxford, England
[4] SUNY Stony Brook, Dept Comp Sci, Stony Brook, NY 11794 USA
基金
英国工程与自然科学研究理事会;
关键词
Software performance and reliability engineering; Probabilistic model synthesis; Multi-objective optimisation; Robust design; PARAMETER SYNTHESIS; SENSITIVITY-ANALYSIS; GENETIC ALGORITHM; SOFTWARE; PERFORMANCE; CHECKING; VERIFICATION; RELIABILITY; QUALITY; DESIGN;
D O I
10.1016/j.jss.2018.05.013
中图分类号
TP31 [计算机软件];
学科分类号
081202 ; 0835 ;
摘要
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.
引用
收藏
页码:140 / 158
页数:19
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