A Survey of Probabilistic Timing Analysis Techniques for Real-Time Systems

Robert Davis (1, 2) , Liliana Cucu-Grosjean (2, 3)

1 University of York [York, UK]
2 AOSTE2 - Models and methods of analysis and optimization for systems with real-time and embedded contraints
3 KOPERNIC - Adapter le raisonnement pire cas à différentes criticités

This survey covers probabilistic timing analysis techniques for real-time systems. It reviews and critiques the key results in the field from its origins in 2000 to the latest research published up to the end of August 2018. The survey provides a taxonomy of the different methods used, and a classification of existing research. A detailed review is provided covering the main subject areas: static probabilistic timing analysis, measurement-based probabilistic timing analysis, and hybrid methods. In addition, research on supporting mechanisms and techniques, case studies, and evaluations is also reviewed. The survey concludes by identifying open issues, key challenges and possible directions for future research.

Mots clés: Probabilistic; Real-time; Timing analysis

Domaines: Systèmes embarqués

Robert Davis, Liliana Cucu-Grosjean. A Survey of Probabilistic Timing Analysis Techniques for Real-Time Systems. Leibniz Transactions on Embedded Systems, 2019, 6 (1), pp.60. ⟨10.4230/LITES-v006-i001-a003⟩. ⟨hal-02158973⟩