A Model-Based Optimization Method of ARINC 653 Multicore Partition Scheduling
ARINC 653 Part 1 Supplement 5 (ARINC 653P1-5) provides temporal partitioning capabilities for real-time applications running on the multicore processors in Integrated Modular Avionics (IMAs) systems. However, it is difficult to schedule a set of ARINC 653 multicore partitions to achieve a minimum pr...
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MDPI AG
2024-11-01
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| author | Pujie Han Wentao Hu Zhengjun Zhai Min Huang |
| author_facet | Pujie Han Wentao Hu Zhengjun Zhai Min Huang |
| author_sort | Pujie Han |
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| description | ARINC 653 Part 1 Supplement 5 (ARINC 653P1-5) provides temporal partitioning capabilities for real-time applications running on the multicore processors in Integrated Modular Avionics (IMAs) systems. However, it is difficult to schedule a set of ARINC 653 multicore partitions to achieve a minimum processor occupancy. This paper proposes a model-based optimization method for ARINC 653 multicore partition scheduling. The IMA multicore processing system is modeled as a network of timed automata in UPPAAL. A parallel genetic algorithm is employed to explore the solution space of the IMA system. Owing to a lack of priori information for the system model, the configuration of genetic operators is self-adaptively controlled by a Q-learning algorithm. During the evolution, each individual in a population is evaluated independently by compositional model checking, which verifies each partition in the IMA system and combines all the schedulability results to form a global fitness evaluation. The experiments show that our model-based method outperforms the traditional analytical methods when handling the same task loads in the ARINC 653 multicore partitions, while alleviating the state space explosion of model checking via parallelization acceleration. |
| format | Article |
| id | doaj-art-8d4c2b640ddc4415a91dbab26b1d09bd |
| institution | OA Journals |
| issn | 2226-4310 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | MDPI AG |
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| series | Aerospace |
| spelling | doaj-art-8d4c2b640ddc4415a91dbab26b1d09bd2025-08-20T02:08:11ZengMDPI AGAerospace2226-43102024-11-01111191510.3390/aerospace11110915A Model-Based Optimization Method of ARINC 653 Multicore Partition SchedulingPujie Han0Wentao Hu1Zhengjun Zhai2Min Huang3College of Software Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaCollege of Software Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaSchool of Computer Science and Engineering, Northwestern Polytechnical University, Xi’an 710072, ChinaCollege of Software Engineering, Zhengzhou University of Light Industry, Zhengzhou 450002, ChinaARINC 653 Part 1 Supplement 5 (ARINC 653P1-5) provides temporal partitioning capabilities for real-time applications running on the multicore processors in Integrated Modular Avionics (IMAs) systems. However, it is difficult to schedule a set of ARINC 653 multicore partitions to achieve a minimum processor occupancy. This paper proposes a model-based optimization method for ARINC 653 multicore partition scheduling. The IMA multicore processing system is modeled as a network of timed automata in UPPAAL. A parallel genetic algorithm is employed to explore the solution space of the IMA system. Owing to a lack of priori information for the system model, the configuration of genetic operators is self-adaptively controlled by a Q-learning algorithm. During the evolution, each individual in a population is evaluated independently by compositional model checking, which verifies each partition in the IMA system and combines all the schedulability results to form a global fitness evaluation. The experiments show that our model-based method outperforms the traditional analytical methods when handling the same task loads in the ARINC 653 multicore partitions, while alleviating the state space explosion of model checking via parallelization acceleration.https://www.mdpi.com/2226-4310/11/11/915ARINC 653model-based optimizationpartition schedulingmulticore processor |
| spellingShingle | Pujie Han Wentao Hu Zhengjun Zhai Min Huang A Model-Based Optimization Method of ARINC 653 Multicore Partition Scheduling Aerospace ARINC 653 model-based optimization partition scheduling multicore processor |
| title | A Model-Based Optimization Method of ARINC 653 Multicore Partition Scheduling |
| title_full | A Model-Based Optimization Method of ARINC 653 Multicore Partition Scheduling |
| title_fullStr | A Model-Based Optimization Method of ARINC 653 Multicore Partition Scheduling |
| title_full_unstemmed | A Model-Based Optimization Method of ARINC 653 Multicore Partition Scheduling |
| title_short | A Model-Based Optimization Method of ARINC 653 Multicore Partition Scheduling |
| title_sort | model based optimization method of arinc 653 multicore partition scheduling |
| topic | ARINC 653 model-based optimization partition scheduling multicore processor |
| url | https://www.mdpi.com/2226-4310/11/11/915 |
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