A framework for the response time analysis of fixed-priority tasks with stochastic inter-arrival times

Cucu, Liliana; Tovar, Eduardo

doi:10.1145/1279711.1279714

Cited by 25 publications

(21 citation statements)

References 5 publications

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“…They introduced a new sporadic task model in which the task arrival may deviate, according to a discrete time probability distribution, from the minimum inter-arrival time. A similar approach is presented in [11]. The work of [24] extends the work in [13] by making all the task attributes probabilistic.…”

Section: Related Workmentioning

confidence: 99%

Flexible Framework for Statistical Schedulability Analysis of Probabilistic Sporadic Tasks

Boudjadar

Kim

David

et al. 2015

2015 IEEE 18th International Symposium on Real-Time Distributed Computing

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Abstract-The analysis of probabilistic schedulability explores all possible combinations of the probabilities of task attributes, which can easily lead to exponential computation time [24]. In this paper, we present a flexible schedulability analysis framework for periodic and sporadic tasks having probabilistic attributes where the computation time scales linearly in the size of analyzed systems. The framework is given in terms of a set of Parameterized Stopwatch Automata (PSA) models, which leads to a large degree of flexibility. Probability distributions for response time are generated using statistical model checking (UPPAAL SMC) while the overall schedulability can be checked using symbolic model checking (UPPAAL). We also define PoMD (percentage of missed deadlines) as a measure of the probabilistic schedulability of systems. To evaluate our approach, we compare the time used for computing response times and the analysis results using similar task models to that of a related analytical approach.

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Section: Related Workmentioning

confidence: 99%

Flexible Framework for Statistical Schedulability Analysis of Probabilistic Sporadic Tasks

Boudjadar

Kim

David

et al. 2015

2015 IEEE 18th International Symposium on Real-Time Distributed Computing

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“…This method was further improved using cache simulation techniques [3]. Comparisons between MBPTA [15] and the SPTA methods based on reuse distance were shown in [1].…”

Section: Related Workmentioning

confidence: 99%

“…external interrupts, network interfaces, etc.. In [15], the authors introduce a framework for computing response time distributions in the case when in the system there are tasks that have random arrivals, given as independent discrete random variables. The rest of the parameters of the tasks are deterministic.…”

Section: Probabilistic Timing Analysismentioning

confidence: 99%

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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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“…A very natural choice is offered by the so-called probabilistic deadlines [5]: a deadline is associated with a probability of meeting it, which in turn is related to the scheduling parameters. Even if probabilistic analysis can be applied to classic real-time scheduling algorithms [6], [7], [8], [9], [10], other scheduling approaches such as the resource reservations [11], [12] are commonly regarded as a superior choice for this class applications because they isolate the temporal behaviour of the tasks and enable a fine grained control on the amount of resources it receives. For this and other reasons, the resource reservations algorithm (and their derivatives) have gained visibility and consideration in the real-time scheduling community.…”

Section: Introductionmentioning

confidence: 99%

Numerically efficient probabilistic guarantees for resource reservations

Manica

Palopoli

Abeni

2012

Proceedings of 2012 IEEE 17th International Conference on Emerging Technologies &Amp; Factory Automation (ETFA 2012)

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Abstract-This paper presents an efficient algorithm for providing probabilistic guarantees in soft real-time systems using resource reservations. We use a conservative model for the temporal evolution of a resource reservation, which has a particular structure -a quasi birth death process -enabling an efficient computation of the stationary probability of respecting deadlines . We show the accuracy and the efficiency of the method in a large set of experiments.

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A framework for the response time analysis of fixed-priority tasks with stochastic inter-arrival times

Cited by 25 publications

References 5 publications

Flexible Framework for Statistical Schedulability Analysis of Probabilistic Sporadic Tasks

Flexible Framework for Statistical Schedulability Analysis of Probabilistic Sporadic Tasks

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

Numerically efficient probabilistic guarantees for resource reservations

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