Latency analysis for data chains of real-time periodic tasks

Kloda, Tomasz; Bertout, Antoine; Sorel, Yves

doi:10.1109/etfa.2018.8502498

Cited by 33 publications

(3 citation statements)

References 24 publications

(28 reference statements)

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“…In this section, we evaluate the performance of the worstcase latency analysis [36] summarized in Section 3 and of the polynomial-time upper bound on the latency presented in Section 4 in terms of precision and practical complexity on a generic automotive benchmark [38] upon a single processor.…”

Section: Methodsmentioning

confidence: 99%

“…In this section, we present a method for computing the maximum latency of the data chains of real-time periodic tasks [36]. First, we characterize the time durations between the releases of a task that writes the data and the next task in the chain that reads this data.…”

Section: Latency Analysismentioning

confidence: 99%

“…Contribution. In our previous work [36], we proposed a method for the computation of the data chain worst-case latency of periodic independent tasks with implicit deadlines scheduled by a fixed-priority preemptive algorithm given a priority assignment of these tasks and their worst-case response times. As the method has exponential time complexity, in this work we:…”

Section: Introductionmentioning

confidence: 99%

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Latency upper bound for data chains of real-time periodic tasks

Kloda

Bertout

Sorel

2020

Journal of Systems Architecture

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The inter-task communication in embedded real-time systems can be achieved using various patterns and be subject to different timing constraints. One of the most basic communication patterns encountered in today's automotive and aerospace software is the data chain. Each task of the chain reads data from the previous task and delivers the results of its computation to the next task. The data passing does not affect the execution of the tasks that are activated periodically at their own rates. As there is no task synchronization, a task does not wait for its predecessor data; it may execute with old data and get new data at its later release. From the design stage of embedded real-time systems, evaluating if data chains meet their timing requirements, such as the latency constraint, is of the highest importance. The trade-off between accuracy and complexity of the timing analysis is a critical element in the optimization process. In this paper, we consider data chains of real-time periodic tasks executed by a fixed-priority preemptive scheduler upon a single processor. We present a method for the worst-case latency calculation of periodic tasks' data chains. As the method has an exponential time complexity, we derive a polynomial-time upper bound. Evaluations carried out on an automotive benchmark demonstrate that the average bound overestimation is less than 10 percent of the actual value.

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Section: Methodsmentioning

confidence: 99%

Section: Latency Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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