The problem of estimating a tight and safe Worst-Case Execution Time (WCET), needed for certification in safety-critical environment, is a challenging problem for modern embedded systems. A possible solution proposed in last years is to exploit statistical tools to obtain a probability distribution of the WCET. These probabilistic real-time analyses for WCET are however subject to errors, even when all the applicability hypotheses are satisfied and verified. This is caused by the uncertainties of the probabilistic-WCET distribution estimator. This article aims at improving the measurement-based probabilistic timing analysis approach providing some techniques to analyze and deal with such uncertainties. The so-called region of acceptance model based on state-of-the-art statistical test procedures is defined over the distribution space parameters. From this model, a set of strategies is derived and discussed, to provide the methodology to deal with the trade-off safety/tightness of the WCET estimation. These techniques are then tested over real datasets, including industrial safety-critical applications, to show the increased value of using the proposed approach in probabilistic WCET analyses.

Dealing with uncertainty in pWCET estimations

Federico Reghenzani;William Fornaciari
2020-01-01

Abstract

The problem of estimating a tight and safe Worst-Case Execution Time (WCET), needed for certification in safety-critical environment, is a challenging problem for modern embedded systems. A possible solution proposed in last years is to exploit statistical tools to obtain a probability distribution of the WCET. These probabilistic real-time analyses for WCET are however subject to errors, even when all the applicability hypotheses are satisfied and verified. This is caused by the uncertainties of the probabilistic-WCET distribution estimator. This article aims at improving the measurement-based probabilistic timing analysis approach providing some techniques to analyze and deal with such uncertainties. The so-called region of acceptance model based on state-of-the-art statistical test procedures is defined over the distribution space parameters. From this model, a set of strategies is derived and discussed, to provide the methodology to deal with the trade-off safety/tightness of the WCET estimation. These techniques are then tested over real datasets, including industrial safety-critical applications, to show the increased value of using the proposed approach in probabilistic WCET analyses.
real-time, WCET, probabilistic worst case execution time, statiscical analysis
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1136575
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