Efficient and robust probabilistic guarantees for real-time tasks
Journal of Systems and Software
Re-sampling for statistical timing analysis of real-time systems
Proceedings of the 20th International Conference on Real-Time and Network Systems
PROARTIS: Probabilistically Analyzable Real-Time Systems
ACM Transactions on Embedded Computing Systems (TECS) - Special Section on Probabilistic Embedded Computing
Challenges and new trends in probabilistic timing analysis
DATE '12 Proceedings of the Conference on Design, Automation and Test in Europe
| Hi-index | 0.00 |
This paper provides a stochastic approach to the analysis of real-time systems under preemptive priority-driven scheduling. The main idea is to simplify the execution time distributions via random sampling to decrease complexity. This beneficial effect is counterbalanced by an increase in pessimism. However, the proposed analysis is significantly less pessimistic than the classical worst-case deterministic analysis. In addition, it could be tuned according to the memory and time availability. Thus, the proposed method provides, for the first time, a relation between pessimism and computational resources. The testing results show the effectiveness of the sampling approach in terms of practicality and optimism.