The Digraph Real-Time Task Model

Stigge, Martin; Ekberg, Pontus; Guan, Nan; Yi, Wang

doi:10.1109/rtas.2011.15

Cited by 129 publications

(144 citation statements)

References 12 publications

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“…This bound is in fact equivalent to the bound derived in [4] for a similar problem concerning the more general digraph real-time task model. Now consider max B .…”

Section: The Value Of Maxsupporting

confidence: 51%

“…The gmf task model is well suited for this because the order in which jobs are released by a single task is fixed, even though the jobs may have differing parameters and non-deterministic release times. This can be contrasted to even more general task models, such as the digraph real-time task model [4], which expresses job releases with an arbitrary directed graph. The non-deterministic branching inherent to such models makes optimal scheduling very hard to achieve when shared resources are considered.…”

Section: Discussionmentioning

confidence: 99%

“…It can be noted that the lack of branching in gmf-r tasks allows us to efficiently make the necessary predictions to achieve optimal scheduling. While the scheduling algorithm we propose could be applied to more general task models that include branching, such as the digraph realtime task model [4] extended with resources, its optimality would be lost. …”

Section: A Motivating Examplementioning

confidence: 99%

“…The absolute-time ceiling protocol by Guan et al [11] handles resource sharing with the digraph real-time task model [4], of which gmf is a special case. That protocol does not provide optimal scheduling, and restricts itself to systems without nested resource accesses.…”

Section: Related Workmentioning

confidence: 99%

See 3 more Smart Citations

An optimal resource sharing protocol for generalized multiframe tasks

Ekberg

Guan

Stigge

et al. 2015

Journal of Logical and Algebraic Methods in Programming

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Many different task models of varying expressiveness have been proposed to capture the timing constraints of real-time workloads. However, techniques for optimal scheduling and exact feasibility analysis of systems with mutuallyexclusive shared resources have been available only for relatively simple task models, such as the sporadic task model. We consider sharing of mutuallyexclusive resources in task models that are more expressive in terms of the jobrelease patterns that can be modeled. We propose a new scheduling algorithm and show that it is optimal for scheduling generalized multiframe tasks with shared resources on uniprocessor systems. We also present an efficient feasibility test for such systems, and show that it is both sufficient and necessary.

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“…This bound is in fact equivalent to the bound derived in [4] for a similar problem concerning the more general digraph real-time task model. Now consider max B .…”

Section: The Value Of Maxsupporting

confidence: 51%

Section: Discussionmentioning

confidence: 99%

Section: A Motivating Examplementioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

An optimal resource sharing protocol for generalized multiframe tasks

Ekberg

Guan

Stigge

et al. 2015

Journal of Logical and Algebraic Methods in Programming

Self Cite

View full text Add to dashboard Cite

show abstract

“…Among them are the multiframe task model [1], its generalized form [2], the recurring real-time task model [3], and the currently most general model, the digraph task model [4]. The digraph task model describes a task with a directed graph.…”

Section: Related Workmentioning

confidence: 99%

Sufficient Real-Time Analysis for an Engine Control Unit with Constant Angular Velocities

Pollex¹,

Feld²,

Slomka³

et al. 2013

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2013

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Abstract-Engine control units in the automotive industry are particular challenging real-time systems regarding their real-time analysis. Some of the tasks of such an engine control unit are triggered by the engine, i.e. the faster the angular velocity of the engine, the more frequent the tasks are executed. Furthermore, the execution time of a task may vary with the angular velocity of the engine. As a result the worst case does not necessarily occur when all tasks are activated simultaneously. Hence this behavior cannot be addressed appropriately with the currently available real-time analysis methods. In this paper we make a first step towards a real-time analysis for an engine control unit. We present a sufficient real-time analysis assuming that the angular velocity of the engine is arbitrary but fixed.

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Probabilistic response‐time analysis for real‐time systems in body area sensor networks

Ren

et al. 2015

Int J Communication

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SUMMARYAdvances in real-time system and wireless communication have led to the deployment of body area sensor networks (BASNs) for effective real-time healthcare applications. Real-time systems in BASNs tend increasingly to be probabilistic and mixed critical to meet stringent requirements on space, weight, and power consumption. Response-time analysis is an important and challenging task for BASNs to provide some critical services. In this paper, we propose a request-based compositional probabilistic response-time analysis framework for probabilistic real-time task models with fixed-priority preemptive scheduling in BASNs. In this method, each probabilistic real-time task is abstracted as a probabilistic request function. Rough response-time distribution is computed first based on the cumulative request distribution and then exact response-time distribution is obtained by refinement based on the request increase distribution. Our strategy can effectively improve performance by reducing repetitive computational overhead for the probabilistic response-time analysis of all tasks in the system. Our evaluation demonstrates that our proposed method significantly outperforms the existing probabilistic response-time analysis algorithm in terms of analysis duration.

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The Digraph Real-Time Task Model

Cited by 129 publications

References 12 publications

An optimal resource sharing protocol for generalized multiframe tasks

An optimal resource sharing protocol for generalized multiframe tasks

Sufficient Real-Time Analysis for an Engine Control Unit with Constant Angular Velocities

Probabilistic response‐time analysis for real‐time systems in body area sensor networks

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