Leveraging weakly-hard constraints for improving system fault tolerance with functional and timing guarantees

Liang, Hengyi; Wang, Zhilu; Jiao, Ruochen; Zhu, Qi

doi:10.1145/3400302.3415717

Cited by 9 publications

(2 citation statements)

References 33 publications

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“…Such an approach tries to minimize the overall execution time of a task by postponing the execution of reliable mode. Liang et al in [28] developed new methods and an optimization algorithm to analyze and improve control stability and system schedulability under deadline misses, faults, and the application of two different fault-tolerance techniques, where redundant execution is applied of EOC [13] techniques and re-execution are performed in case of a soft error. In addition, to maintain the control quality and ensure the schedulability, skipping certain control computation is considered.…”

Section: Related Workmentioning

confidence: 99%

Average Task Execution Time Minimization under (m, k) Soft Error Constraint

Shi

Ueter

Chen

et al. 2023

2023 IEEE 29th Real-Time and Embedded Technology and Applications Symposium (RTAS)

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Safety-critical systems are often subjected to transient faults. Since these transient faults may lead to soft errors that cause catastrophic consequences, error-handling must be addressed by design. Full-protection against faults is too costly in terms of resource usage. A common approach to relax the resource demands and limit the impact of errors is to consider (m, k)-constraints, which requires that at least m jobs out of any k consecutive jobs are error-free. To assure (m, k)-compliance, static patterns are widely used to select the job execution modes, i.e., either in an error-free mode at the cost of increased worst-case execution time or in an error-prone mode with the advantage of less execution time. Although static patterns have been shown to be effective in energy-aware designs, resource over-provision is inevitable due to the relatively low rate of error probability. In this work, we propose two dynamic (and adaptive) approaches that allow the scheduler to opportunistically select execution modes based on the error-history of the past jobs and the actual error probability. We firstly propose a Markov chain based solution if the error-probability is known and static and secondly a reinforcement learning-based approach that can handle unknown error probabilities. Experimental evaluations show that our approaches outperform the state-of-the-art in most of the evaluated cases in terms of average utilization for each task and the overall utilization for multitask systems.1 2023 IEEE 29th Real-Time and Embedded Technology and Applications Symposium (RTAS)

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Section: Related Workmentioning

confidence: 99%

Average Task Execution Time Minimization under (m, k) Soft Error Constraint

Shi

Ueter

Chen

et al. 2023

2023 IEEE 29th Real-Time and Embedded Technology and Applications Symposium (RTAS)

View full text Add to dashboard Cite

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“…This model is equivalent to the case where deadline misses represent discarded computations, but its results can not be generalized for the other common case of late completions. In other works [23], [28], [29], the authors have studied how to enforce safety guarantees of weakly-hard real-time controllers, with focus also on stability properties. However, such works consider only the case where a deadline miss corresponds to a discarded computation and, in [28], [29], with the additional hypothesis of a known periodic pattern of deadline hits and misses.…”

Section: Introductionmentioning

confidence: 99%

Stability of Control Systems under Extended Weakly-Hard Constraints

Vreman¹,

Pazzaglia²,

Wang³

et al. 2021

Preprint

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Control systems can show robustness to many events, like disturbances and model inaccuracies. It is natural to speculate that they are also robust to alterations of the control signal pattern, due to sporadic late completions (called deadline misses) when implemented as a digital task on an embedded platform. Recent research analysed stability when imposing constraints on the maximum number of consecutive deadlines that can be missed. This is only one type of characterization, and results in a pessimistic analysis when applied to more general cases. To overcome this limitation, this paper proposes a comprehensive stability analysis for control systems subject to a set of generic constraints, describing the possible sequences of correct completions and deadline misses. The proposed analysis brings the assessment of control systems robustness to computational problems one step closer to the controller implementation.

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