The concept of Maximal Unschedulable Deadline Assignment for optimization in fixed-priority scheduled real-time systems
Abstract This paper considers the problem of design optimization for real-time systems scheduled with fixed priority, where task priority assignment is part of the decision variables, and the timing constraints and/or objective function linearly depend on the exact value of task response times (such...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Zhao, Yecheng [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2019 |
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| Schlagwörter: |
Average worst-case response time Maximal Unschedulable Deadline Assignment (MUDA) |
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| Anmerkung: |
© Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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| Übergeordnetes Werk: |
Enthalten in: Real-time systems - Springer US, 1989, 55(2019), 3 vom: 26. Feb., Seite 667-707 |
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| Übergeordnetes Werk: |
volume:55 ; year:2019 ; number:3 ; day:26 ; month:02 ; pages:667-707 |
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| DOI / URN: |
10.1007/s11241-019-09332-0 |
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OLC2054362034 |
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| 520 | |a Abstract This paper considers the problem of design optimization for real-time systems scheduled with fixed priority, where task priority assignment is part of the decision variables, and the timing constraints and/or objective function linearly depend on the exact value of task response times (such as end-to-end deadline constraints). The complexity of response time analysis techniques makes it difficult to leverage existing optimization frameworks and scale to large designs. Instead, we propose an efficient optimization framework that is three orders of magnitude (1000 times) faster than Integer Linear Programming (ILP) while providing solutions with the same quality. The framework centers around three novel ideas: (1) an efficient algorithm that finds a schedulable task priority assignment for minimizing the average worst-case response time; (2) the concept of Maximal Unschedulable Deadline Assignment (MUDA) that abstracts the schedulability conditions, i.e., a set of maximal virtual deadline assignments such that the system is unschedulable; and (3) a new optimization procedure that leverages the concept of MUDA and the efficient algorithm to compute it. | ||
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10.1007/s11241-019-09332-0 doi (DE-627)OLC2054362034 (DE-He213)s11241-019-09332-0-p DE-627 ger DE-627 rakwb eng 004 VZ Zhao, Yecheng verfasserin aut The concept of Maximal Unschedulable Deadline Assignment for optimization in fixed-priority scheduled real-time systems 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract This paper considers the problem of design optimization for real-time systems scheduled with fixed priority, where task priority assignment is part of the decision variables, and the timing constraints and/or objective function linearly depend on the exact value of task response times (such as end-to-end deadline constraints). The complexity of response time analysis techniques makes it difficult to leverage existing optimization frameworks and scale to large designs. Instead, we propose an efficient optimization framework that is three orders of magnitude (1000 times) faster than Integer Linear Programming (ILP) while providing solutions with the same quality. The framework centers around three novel ideas: (1) an efficient algorithm that finds a schedulable task priority assignment for minimizing the average worst-case response time; (2) the concept of Maximal Unschedulable Deadline Assignment (MUDA) that abstracts the schedulability conditions, i.e., a set of maximal virtual deadline assignments such that the system is unschedulable; and (3) a new optimization procedure that leverages the concept of MUDA and the efficient algorithm to compute it. Average worst-case response time Maximal Unschedulable Deadline Assignment (MUDA) Schedulability condition abstraction Design optimization Zeng, Haibo (orcid)0000-0003-1162-759X aut Enthalten in Real-time systems Springer US, 1989 55(2019), 3 vom: 26. Feb., Seite 667-707 (DE-627)130955892 (DE-600)1064543-3 (DE-576)025100394 0922-6443 nnns volume:55 year:2019 number:3 day:26 month:02 pages:667-707 https://doi.org/10.1007/s11241-019-09332-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_4036 AR 55 2019 3 26 02 667-707 |
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10.1007/s11241-019-09332-0 doi (DE-627)OLC2054362034 (DE-He213)s11241-019-09332-0-p DE-627 ger DE-627 rakwb eng 004 VZ Zhao, Yecheng verfasserin aut The concept of Maximal Unschedulable Deadline Assignment for optimization in fixed-priority scheduled real-time systems 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract This paper considers the problem of design optimization for real-time systems scheduled with fixed priority, where task priority assignment is part of the decision variables, and the timing constraints and/or objective function linearly depend on the exact value of task response times (such as end-to-end deadline constraints). The complexity of response time analysis techniques makes it difficult to leverage existing optimization frameworks and scale to large designs. Instead, we propose an efficient optimization framework that is three orders of magnitude (1000 times) faster than Integer Linear Programming (ILP) while providing solutions with the same quality. The framework centers around three novel ideas: (1) an efficient algorithm that finds a schedulable task priority assignment for minimizing the average worst-case response time; (2) the concept of Maximal Unschedulable Deadline Assignment (MUDA) that abstracts the schedulability conditions, i.e., a set of maximal virtual deadline assignments such that the system is unschedulable; and (3) a new optimization procedure that leverages the concept of MUDA and the efficient algorithm to compute it. Average worst-case response time Maximal Unschedulable Deadline Assignment (MUDA) Schedulability condition abstraction Design optimization Zeng, Haibo (orcid)0000-0003-1162-759X aut Enthalten in Real-time systems Springer US, 1989 55(2019), 3 vom: 26. Feb., Seite 667-707 (DE-627)130955892 (DE-600)1064543-3 (DE-576)025100394 0922-6443 nnns volume:55 year:2019 number:3 day:26 month:02 pages:667-707 https://doi.org/10.1007/s11241-019-09332-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_4036 AR 55 2019 3 26 02 667-707 |
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10.1007/s11241-019-09332-0 doi (DE-627)OLC2054362034 (DE-He213)s11241-019-09332-0-p DE-627 ger DE-627 rakwb eng 004 VZ Zhao, Yecheng verfasserin aut The concept of Maximal Unschedulable Deadline Assignment for optimization in fixed-priority scheduled real-time systems 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract This paper considers the problem of design optimization for real-time systems scheduled with fixed priority, where task priority assignment is part of the decision variables, and the timing constraints and/or objective function linearly depend on the exact value of task response times (such as end-to-end deadline constraints). The complexity of response time analysis techniques makes it difficult to leverage existing optimization frameworks and scale to large designs. Instead, we propose an efficient optimization framework that is three orders of magnitude (1000 times) faster than Integer Linear Programming (ILP) while providing solutions with the same quality. The framework centers around three novel ideas: (1) an efficient algorithm that finds a schedulable task priority assignment for minimizing the average worst-case response time; (2) the concept of Maximal Unschedulable Deadline Assignment (MUDA) that abstracts the schedulability conditions, i.e., a set of maximal virtual deadline assignments such that the system is unschedulable; and (3) a new optimization procedure that leverages the concept of MUDA and the efficient algorithm to compute it. Average worst-case response time Maximal Unschedulable Deadline Assignment (MUDA) Schedulability condition abstraction Design optimization Zeng, Haibo (orcid)0000-0003-1162-759X aut Enthalten in Real-time systems Springer US, 1989 55(2019), 3 vom: 26. Feb., Seite 667-707 (DE-627)130955892 (DE-600)1064543-3 (DE-576)025100394 0922-6443 nnns volume:55 year:2019 number:3 day:26 month:02 pages:667-707 https://doi.org/10.1007/s11241-019-09332-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_4036 AR 55 2019 3 26 02 667-707 |
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10.1007/s11241-019-09332-0 doi (DE-627)OLC2054362034 (DE-He213)s11241-019-09332-0-p DE-627 ger DE-627 rakwb eng 004 VZ Zhao, Yecheng verfasserin aut The concept of Maximal Unschedulable Deadline Assignment for optimization in fixed-priority scheduled real-time systems 2019 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © Springer Science+Business Media, LLC, part of Springer Nature 2019 Abstract This paper considers the problem of design optimization for real-time systems scheduled with fixed priority, where task priority assignment is part of the decision variables, and the timing constraints and/or objective function linearly depend on the exact value of task response times (such as end-to-end deadline constraints). The complexity of response time analysis techniques makes it difficult to leverage existing optimization frameworks and scale to large designs. Instead, we propose an efficient optimization framework that is three orders of magnitude (1000 times) faster than Integer Linear Programming (ILP) while providing solutions with the same quality. The framework centers around three novel ideas: (1) an efficient algorithm that finds a schedulable task priority assignment for minimizing the average worst-case response time; (2) the concept of Maximal Unschedulable Deadline Assignment (MUDA) that abstracts the schedulability conditions, i.e., a set of maximal virtual deadline assignments such that the system is unschedulable; and (3) a new optimization procedure that leverages the concept of MUDA and the efficient algorithm to compute it. Average worst-case response time Maximal Unschedulable Deadline Assignment (MUDA) Schedulability condition abstraction Design optimization Zeng, Haibo (orcid)0000-0003-1162-759X aut Enthalten in Real-time systems Springer US, 1989 55(2019), 3 vom: 26. Feb., Seite 667-707 (DE-627)130955892 (DE-600)1064543-3 (DE-576)025100394 0922-6443 nnns volume:55 year:2019 number:3 day:26 month:02 pages:667-707 https://doi.org/10.1007/s11241-019-09332-0 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_4036 AR 55 2019 3 26 02 667-707 |
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Abstract This paper considers the problem of design optimization for real-time systems scheduled with fixed priority, where task priority assignment is part of the decision variables, and the timing constraints and/or objective function linearly depend on the exact value of task response times (such as end-to-end deadline constraints). The complexity of response time analysis techniques makes it difficult to leverage existing optimization frameworks and scale to large designs. Instead, we propose an efficient optimization framework that is three orders of magnitude (1000 times) faster than Integer Linear Programming (ILP) while providing solutions with the same quality. The framework centers around three novel ideas: (1) an efficient algorithm that finds a schedulable task priority assignment for minimizing the average worst-case response time; (2) the concept of Maximal Unschedulable Deadline Assignment (MUDA) that abstracts the schedulability conditions, i.e., a set of maximal virtual deadline assignments such that the system is unschedulable; and (3) a new optimization procedure that leverages the concept of MUDA and the efficient algorithm to compute it. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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Abstract This paper considers the problem of design optimization for real-time systems scheduled with fixed priority, where task priority assignment is part of the decision variables, and the timing constraints and/or objective function linearly depend on the exact value of task response times (such as end-to-end deadline constraints). The complexity of response time analysis techniques makes it difficult to leverage existing optimization frameworks and scale to large designs. Instead, we propose an efficient optimization framework that is three orders of magnitude (1000 times) faster than Integer Linear Programming (ILP) while providing solutions with the same quality. The framework centers around three novel ideas: (1) an efficient algorithm that finds a schedulable task priority assignment for minimizing the average worst-case response time; (2) the concept of Maximal Unschedulable Deadline Assignment (MUDA) that abstracts the schedulability conditions, i.e., a set of maximal virtual deadline assignments such that the system is unschedulable; and (3) a new optimization procedure that leverages the concept of MUDA and the efficient algorithm to compute it. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
| abstract_unstemmed |
Abstract This paper considers the problem of design optimization for real-time systems scheduled with fixed priority, where task priority assignment is part of the decision variables, and the timing constraints and/or objective function linearly depend on the exact value of task response times (such as end-to-end deadline constraints). The complexity of response time analysis techniques makes it difficult to leverage existing optimization frameworks and scale to large designs. Instead, we propose an efficient optimization framework that is three orders of magnitude (1000 times) faster than Integer Linear Programming (ILP) while providing solutions with the same quality. The framework centers around three novel ideas: (1) an efficient algorithm that finds a schedulable task priority assignment for minimizing the average worst-case response time; (2) the concept of Maximal Unschedulable Deadline Assignment (MUDA) that abstracts the schedulability conditions, i.e., a set of maximal virtual deadline assignments such that the system is unschedulable; and (3) a new optimization procedure that leverages the concept of MUDA and the efficient algorithm to compute it. © Springer Science+Business Media, LLC, part of Springer Nature 2019 |
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The concept of Maximal Unschedulable Deadline Assignment for optimization in fixed-priority scheduled real-time systems |
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