Stochastic analysis of real-time systems under preemptive priority-driven scheduling

López, José M.; Díaz, José Luis Gahete; Entrialgo, Joaquín; García, Daniel

doi:10.1007/s11241-008-9053-6

Cited by 52 publications

(36 citation statements)

References 17 publications

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“…The next step towards an exact probabilistic analysis was made by [22] with the introduction of the Stochastic Time Demand Analysis (STDA) for tasks that have probabilistic execution times, computing a lower bound on the probability that jobs of each task will meet their respective deadlines. Later on, [21], [29], [32] refined STDA into an exact analysis for real-time systems that have random execution times. The execution time is represented as a general random variable and the priorities may be job-level or task-level.…”

Section: Probabilistic Timing Analysismentioning

confidence: 99%

Study of the reliability of statistical timing analysis for real-time systems

Maxim¹,

Soboczenski

Bate

et al. 2015

Proceedings of the 23rd International Conference on Real Time and Networks Systems

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Probabilistic and statistical temporal analyses have been developedas a means of determining the worst-case execution and responsetimes of real-time software for decades. A number of such methodshave been proposed in the literature, of which the majority claim tobe able to provide worst-case timing scenarios with respect to agiven likelihood of a certain value being exceeded. Further, suchclaims are based on either some estimates associated with a probability,or probability distributions with a certain level of confidence.However, the validity of the claims are very much dependent on anumber of factors, such as the achieved samples and the adopteddistributions for analysis.In this paper, we investigate whether the claims made are in facttrue as well as the establishing an understanding of the factors thataffect the validity of these claims. The results are of importancefor two reasons: to allow researchers to examine whether there areimportant issues that mean their techniques need to be refined; andso that practitioners, including industrialists who are currently usingcommercial timing analysis tools based on these types of techniques,understand how the techniques should be used to ensure theresults are fit for their purposes. Study of the Reliability of Statistical Timing Analysis forReal-Time Systems ABSTRACTProbabilistic and statistical temporal analyses have been developed as a means of determining the worst-case execution and response times of real-time software for decades. A number of such methods have been proposed in the literature, of which the majority claim to be able to provide worst-case timing scenarios with respect to a given likelihood of a certain value being exceeded. Further, such claims are based on either some estimates associated with a probability, or probability distributions with a certain level of confidence. However, the validity of the claims are very much dependent on a number of factors, such as the achieved samples and the adopted distributions for analysis. This paper is the first one that puts side by side existing state of the art statistical and probabilistic analysis techniques, using the probabilistic analysis as the ground truth in order to asses the applicability and performance of the statistical technique. The evaluation clearly shows that for the experiments performed the approach can identify clear differences between a range of techniques and that these differences can be considered valid based on the trends expected from the academic theory.

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Section: Probabilistic Timing Analysismentioning

confidence: 99%

Study of the reliability of statistical timing analysis for real-time systems

Maxim¹,

Soboczenski

Bate

et al. 2015

Proceedings of the 23rd International Conference on Real Time and Networks Systems

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“…In [4,18] the authors provide the calculation of the probabilistic response time of a job under a preemptive uniprocessor fixedpriority scheduling policy as given by Equation (2).…”

Section: Probabilistic Real-time Analysismentioning

confidence: 99%

“…Here Wi,j(λi,j) is the backlog at time λi,j obtained as the workload of higher priority jobs than τi,j that have not yet been executed immediately prior to λi,j. Equation (2) is solved iteratively in [18]. Ci is the execution time of job τi,j and Ii,j is the interference in τi,j of all higher priority jobs than τi,j, hp(i), released at or after τi,j,…”

Section: Probabilistic Real-time Analysismentioning

confidence: 99%

“…First re-sampling techniques have been presented in [16,18,20], stating the necessity and the basic mechanism, but without a thorough analysis of its effects on the response time. The re-sampling techniques we propose simplify the original distribution of WCETs but also take into account the pessimism that the operation introduces to the analysis.…”

Section: Re-sampling: Simplifying Distri-butionsmentioning

confidence: 99%

“…We then say that a re-sampled distribution is safe, from the real-time analysis perspective if it is pessimistic with respect to the original distribution. In order to compare two distributions (original and re-sampled or two re-sampled distributions), we recall here the ordering relationship defined in [18]. DEFINITION 3.3 (ORDER AMONGST RANDOM VARIABLES [18]).…”

Section: Safeness At Execution Time Levelmentioning

confidence: 99%

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Re-sampling for statistical timing analysis of real-time systems

Maxim

Houston

Santinelli

et al. 2012

Proceedings of the 20th International Conference on Real-Time and Network Systems

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Guaranteeing timing constraints is the main purpose of analyses for real-time systems. The satisfaction of these constraints may be verified with probabilistic methods (relying on statistical estimations of certain task parameters) offering both hard and soft guarantees. In this paper, we address the problem of sampling applied to the distributions of worst-case execution times. The pessimism of presented sampling techniques is then evaluated at the level of response times.

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