DAG-based scheduling models have been shown to effectively express the parallel execution of current many-core heterogeneous architectures. However, their applicability to real-time settings is limited by the difficulties to find tight estimations of the worst-case timing parameters of tasks that may arbitrarily be preempted/migrated at any instruction. An efficient approach to increase the system predictability is to limit task preemptions to a set of pre-defined points. This limited preemption model supports two different preemption approaches, eager and lazy, which have been analyzed only for sequential task-sets. This paper proposes a new response time analysis that computes an upper bound on the lower priority blocking that each task may incur with eager and lazy preemptions. We evaluate our analysis with both, synthetic DAG-based task-sets and a real case-study from the automotive domain. Results from the analysis demonstrate that, despite the eager approach generates a higher number of priority inversions, the blocking impact is generally smaller than in the lazy approach, leading to a better schedulability performance.

An analysis of lazy and eager limited preemption approaches under DAG-based global fixed priority scheduling / Serrano, M. A.; Melani, A.; Kehr, S.; Bertogna, M.; Quinones, E.. - (2017), pp. 193-202. (Intervento presentato al convegno 20th IEEE International Symposium on Real-Time Distributed Computing, ISORC 2017 tenutosi a Fields Institute, can nel 2017) [10.1109/ISORC.2017.9].

An analysis of lazy and eager limited preemption approaches under DAG-based global fixed priority scheduling

Bertogna M.;
2017

Abstract

DAG-based scheduling models have been shown to effectively express the parallel execution of current many-core heterogeneous architectures. However, their applicability to real-time settings is limited by the difficulties to find tight estimations of the worst-case timing parameters of tasks that may arbitrarily be preempted/migrated at any instruction. An efficient approach to increase the system predictability is to limit task preemptions to a set of pre-defined points. This limited preemption model supports two different preemption approaches, eager and lazy, which have been analyzed only for sequential task-sets. This paper proposes a new response time analysis that computes an upper bound on the lower priority blocking that each task may incur with eager and lazy preemptions. We evaluate our analysis with both, synthetic DAG-based task-sets and a real case-study from the automotive domain. Results from the analysis demonstrate that, despite the eager approach generates a higher number of priority inversions, the blocking impact is generally smaller than in the lazy approach, leading to a better schedulability performance.
2017
20th IEEE International Symposium on Real-Time Distributed Computing, ISORC 2017
Fields Institute, can
2017
193
202
Serrano, M. A.; Melani, A.; Kehr, S.; Bertogna, M.; Quinones, E.
An analysis of lazy and eager limited preemption approaches under DAG-based global fixed priority scheduling / Serrano, M. A.; Melani, A.; Kehr, S.; Bertogna, M.; Quinones, E.. - (2017), pp. 193-202. (Intervento presentato al convegno 20th IEEE International Symposium on Real-Time Distributed Computing, ISORC 2017 tenutosi a Fields Institute, can nel 2017) [10.1109/ISORC.2017.9].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11380/1222830
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