Quantitative evaluation of real-time systems demands for analysis frameworks that go beyond worst-case assumptions, since some parameters could be better characterized by a random variable than by a deterministic value. On the one hand, this opens notable issues on the safe estimation of probabilistic parameters starting from real measurements. On the other hand, this also requires modeling formalisms and solution techniques that can encompass stochastic temporal parameters with a non-Markovian distribution, thus breaking the limits of Markovian approaches. We propose a framework for modeling and evaluating periodic real-time tasks that may have a probabilistic Worst Case Execution Time (pWCET) and are scheduled by a fixed-priority non-preemptive policy. The methodology leverages the Extreme Value Theory (EVT) for the derivation of the pWCET of tasks by means of Erlang distributions. Evaluation is performed through regenerative transient analysis based on the method of stochastic state classes, supporting the derivation of quantitative measures on the time by which a deadline is missed. The approach is experimented on a case study including tasks with a pWCET derived from benchmarks and real system execution.
Probabilistic Deadline Miss Analysis of Real-Time Systems Using Regenerative Transient Analysis / Laura Carnevali; Alessandra Melani; Luca Santinelli; Giuseppe Lipari. - ELETTRONICO. - (2014), pp. 299-308. (Intervento presentato al convegno International Conference on Real-Time Networks and Systems tenutosi a Versailles nel ottobre 2014) [10.1145/2659787.2659823].
Probabilistic Deadline Miss Analysis of Real-Time Systems Using Regenerative Transient Analysis
CARNEVALI, LAURA;
2014
Abstract
Quantitative evaluation of real-time systems demands for analysis frameworks that go beyond worst-case assumptions, since some parameters could be better characterized by a random variable than by a deterministic value. On the one hand, this opens notable issues on the safe estimation of probabilistic parameters starting from real measurements. On the other hand, this also requires modeling formalisms and solution techniques that can encompass stochastic temporal parameters with a non-Markovian distribution, thus breaking the limits of Markovian approaches. We propose a framework for modeling and evaluating periodic real-time tasks that may have a probabilistic Worst Case Execution Time (pWCET) and are scheduled by a fixed-priority non-preemptive policy. The methodology leverages the Extreme Value Theory (EVT) for the derivation of the pWCET of tasks by means of Erlang distributions. Evaluation is performed through regenerative transient analysis based on the method of stochastic state classes, supporting the derivation of quantitative measures on the time by which a deadline is missed. The approach is experimented on a case study including tasks with a pWCET derived from benchmarks and real system execution.File | Dimensione | Formato | |
---|---|---|---|
RTNS14.pdf
Accesso chiuso
Tipologia:
Pdf editoriale (Version of record)
Licenza:
Tutti i diritti riservati
Dimensione
921.35 kB
Formato
Adobe PDF
|
921.35 kB | Adobe PDF | Richiedi una copia |
I documenti in FLORE sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.