Measurement-based WCET methods are reliable as long as we know all the application behaviors at design-time. In particular, we need to observe all the possible execution time behaviors before the actual system run-time to get a reliable estimation. This is, unfortunately, difficult to achieve. In this work, we propose an online monitoring framework with the goal to detect, at run-time, unexpected application behaviors and trigger the probabilistic-WCET re-estimation when needed. The online monitoring and estimation framework allows dealing with unexpected situations, such as never-seen applications, faults, or incorrect offline estimations. The proposed approach is tested with simulated and real data.

Work-in-Progress: Run-time pWCET Estimation and Quality Monitoring

Federico Reghenzani;Filippo Sciamanna;William Fornaciari
2021-01-01

Abstract

Measurement-based WCET methods are reliable as long as we know all the application behaviors at design-time. In particular, we need to observe all the possible execution time behaviors before the actual system run-time to get a reliable estimation. This is, unfortunately, difficult to achieve. In this work, we propose an online monitoring framework with the goal to detect, at run-time, unexpected application behaviors and trigger the probabilistic-WCET re-estimation when needed. The online monitoring and estimation framework allows dealing with unexpected situations, such as never-seen applications, faults, or incorrect offline estimations. The proposed approach is tested with simulated and real data.
2021
2021 IEEE Real-Time Systems Symposium (RTSS)
probabilistic real-time, pWCET, runtime monitoring
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1185182
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