An Exact Schedulability Test for Real-Time Systems with Abstract Scheduler on Multiprocessor Platforms

This paper uses the model checking method for an exact schedulability test of real-time systems running on multiprocessor platforms. To use this method, we formally describe real-time systems with an abstract scheduler as Kripke models. This formalization provides terms sufficient to specialize the abstract scheduler. We illustrate our approach by explicitly defining schedulers that take into account preemption/non-preemption of tasks and global fixed or earliest-deadline-first priority in various combinations. The safety (schedulability) property of real-time systems is formulated using linear temporal logic LTL. Formalizing real-time systems as Kripke models and specifying the safety (schedulability) property as an LTL formula allows us to reduce the exact schedulability test of such systems to a model checking problem. We validate this approach to an exact schedulability test by implementing our formalization of real-time systems with non-preemptive global fixed-priority (NP-GFP), preemptive global fixed-priority (P-GFP), non-preemptive earliest-deadline-first priority (NP-EDF), and preemptive earliest-deadline-first priority (P-EDF) schedulers in Promela, the input language of the model checking tool SPIN. We conduct experiments in SPIN to prove/disprove the safety (schedulability) property to evaluate the effectiveness of our approach. We propose a heuristic assessment of the schedulability of a real-time system based on the provability of unsafety and unprovability of safety of a real-time system executed on multiprocessor platforms with the number of processors differing by one.

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Publication Details

Journal
Modeling and Analysis of Information Systems
Published
2024-12-13
DOI
https://doi.org/10.18255/1818-1015-2024-4-474-494
Citations
1
Primary Topic
Real-Time Systems Scheduling
Type
article
Field-Weighted Citation Impact
0.49
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article

An Exact Schedulability Test for Real-Time Systems with Abstract Scheduler on Multiprocessor Platforms

Natalia Garanina
1 citations
Modeling and Analysis of Information Systems
Real-Time Systems Scheduling
0.49
article

An Exact Schedulability Test for Real-Time Systems with Abstract Scheduler on Multiprocessor Platforms

Natalia Garanina
article en
1 citations

Abstract

This paper uses the model checking method for an exact schedulability test of real-time systems running on multiprocessor platforms. To use this method, we formally describe real-time systems with an abstract scheduler as Kripke models. This formalization provides terms sufficient to specialize the abstract scheduler. We illustrate our approach by explicitly defining schedulers that take into account preemption/non-preemption of tasks and global fixed or earliest-deadline-first priority in various combinations. The safety (schedulability) property of real-time systems is formulated using linear temporal logic LTL. Formalizing real-time systems as Kripke models and specifying the safety (schedulability) property as an LTL formula allows us to reduce the exact schedulability test of such systems to a model checking problem. We validate this approach to an exact schedulability test by implementing our formalization of real-time systems with non-preemptive global fixed-priority (NP-GFP), preemptive global fixed-priority (P-GFP), non-preemptive earliest-deadline-first priority (NP-EDF), and preemptive earliest-deadline-first priority (P-EDF) schedulers in Promela, the input language of the model checking tool SPIN. We conduct experiments in SPIN to prove/disprove the safety (schedulability) property to evaluate the effectiveness of our approach. We propose a heuristic assessment of the schedulability of a real-time system based on the provability of unsafety and unprovability of safety of a real-time system executed on multiprocessor platforms with the number of processors differing by one.

Modeling and Analysis of Information SystemsVol. 31(4)
Institute of Automation and Electrometry (RU)
Openalex Percentile: Top 33%
Real-Time Systems Scheduling
0.49
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