A framework for multi-core schedulability analysis accounting for resource stress and sensitivity
Abstract Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on res...
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Gespeichert in:
| Autor*in: |
Davis, Robert I. [verfasserIn] |
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| Format: |
Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2022 |
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| Schlagwörter: |
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| Anmerkung: |
© The Author(s) 2022 |
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| Übergeordnetes Werk: |
Enthalten in: Real-time systems - Springer US, 1989, 58(2022), 4 vom: 19. Feb., Seite 456-508 |
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| Übergeordnetes Werk: |
volume:58 ; year:2022 ; number:4 ; day:19 ; month:02 ; pages:456-508 |
| Links: |
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| DOI / URN: |
10.1007/s11241-022-09377-8 |
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OLC2080038648 |
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| 520 | |a Abstract Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on resources and how much it is sensitive to such resource stress. This model facilitates a separation of concerns, thus retaining the advantages of the traditional two-step approach to timing verification (i.e. timing analysis followed by schedulability analysis). Response time analysis is derived for the MRSS task model, providing efficient context-dependent and context independent schedulability tests for both fixed priority preemptive and fixed priority non-preemptive scheduling. Dominance relations are derived between the tests, along with complexity results, and proofs of optimal priority assignment policies. The MRSS task model is underpinned by a proof-of-concept industrial case study. The problem of task allocation is considered in the context of the MRSS task model, with Simulated Annealing shown to provide an effective solution. | ||
| 650 | 4 | |a Schedulability analysis | |
| 650 | 4 | |a Multi-core | |
| 650 | 4 | |a Cross-core contention | |
| 650 | 4 | |a Interference | |
| 650 | 4 | |a Partitioned scheduling | |
| 650 | 4 | |a Fixed priority preemptive scheduling | |
| 650 | 4 | |a Fixed priority non-preemptive scheduling | |
| 700 | 1 | |a Griffin, David |4 aut | |
| 700 | 1 | |a Bate, Iain |4 aut | |
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10.1007/s11241-022-09377-8 doi (DE-627)OLC2080038648 (DE-He213)s11241-022-09377-8-p DE-627 ger DE-627 rakwb eng 004 VZ Davis, Robert I. verfasserin (orcid)0000-0002-5772-0928 aut A framework for multi-core schedulability analysis accounting for resource stress and sensitivity 2022 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2022 Abstract Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on resources and how much it is sensitive to such resource stress. This model facilitates a separation of concerns, thus retaining the advantages of the traditional two-step approach to timing verification (i.e. timing analysis followed by schedulability analysis). Response time analysis is derived for the MRSS task model, providing efficient context-dependent and context independent schedulability tests for both fixed priority preemptive and fixed priority non-preemptive scheduling. Dominance relations are derived between the tests, along with complexity results, and proofs of optimal priority assignment policies. The MRSS task model is underpinned by a proof-of-concept industrial case study. The problem of task allocation is considered in the context of the MRSS task model, with Simulated Annealing shown to provide an effective solution. Schedulability analysis Multi-core Cross-core contention Interference Partitioned scheduling Fixed priority preemptive scheduling Fixed priority non-preemptive scheduling Griffin, David aut Bate, Iain aut Enthalten in Real-time systems Springer US, 1989 58(2022), 4 vom: 19. Feb., Seite 456-508 (DE-627)130955892 (DE-600)1064543-3 (DE-576)025100394 0922-6443 nnns volume:58 year:2022 number:4 day:19 month:02 pages:456-508 https://doi.org/10.1007/s11241-022-09377-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_4036 AR 58 2022 4 19 02 456-508 |
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10.1007/s11241-022-09377-8 doi (DE-627)OLC2080038648 (DE-He213)s11241-022-09377-8-p DE-627 ger DE-627 rakwb eng 004 VZ Davis, Robert I. verfasserin (orcid)0000-0002-5772-0928 aut A framework for multi-core schedulability analysis accounting for resource stress and sensitivity 2022 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2022 Abstract Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on resources and how much it is sensitive to such resource stress. This model facilitates a separation of concerns, thus retaining the advantages of the traditional two-step approach to timing verification (i.e. timing analysis followed by schedulability analysis). Response time analysis is derived for the MRSS task model, providing efficient context-dependent and context independent schedulability tests for both fixed priority preemptive and fixed priority non-preemptive scheduling. Dominance relations are derived between the tests, along with complexity results, and proofs of optimal priority assignment policies. The MRSS task model is underpinned by a proof-of-concept industrial case study. The problem of task allocation is considered in the context of the MRSS task model, with Simulated Annealing shown to provide an effective solution. Schedulability analysis Multi-core Cross-core contention Interference Partitioned scheduling Fixed priority preemptive scheduling Fixed priority non-preemptive scheduling Griffin, David aut Bate, Iain aut Enthalten in Real-time systems Springer US, 1989 58(2022), 4 vom: 19. Feb., Seite 456-508 (DE-627)130955892 (DE-600)1064543-3 (DE-576)025100394 0922-6443 nnns volume:58 year:2022 number:4 day:19 month:02 pages:456-508 https://doi.org/10.1007/s11241-022-09377-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_4036 AR 58 2022 4 19 02 456-508 |
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10.1007/s11241-022-09377-8 doi (DE-627)OLC2080038648 (DE-He213)s11241-022-09377-8-p DE-627 ger DE-627 rakwb eng 004 VZ Davis, Robert I. verfasserin (orcid)0000-0002-5772-0928 aut A framework for multi-core schedulability analysis accounting for resource stress and sensitivity 2022 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2022 Abstract Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on resources and how much it is sensitive to such resource stress. This model facilitates a separation of concerns, thus retaining the advantages of the traditional two-step approach to timing verification (i.e. timing analysis followed by schedulability analysis). Response time analysis is derived for the MRSS task model, providing efficient context-dependent and context independent schedulability tests for both fixed priority preemptive and fixed priority non-preemptive scheduling. Dominance relations are derived between the tests, along with complexity results, and proofs of optimal priority assignment policies. The MRSS task model is underpinned by a proof-of-concept industrial case study. The problem of task allocation is considered in the context of the MRSS task model, with Simulated Annealing shown to provide an effective solution. Schedulability analysis Multi-core Cross-core contention Interference Partitioned scheduling Fixed priority preemptive scheduling Fixed priority non-preemptive scheduling Griffin, David aut Bate, Iain aut Enthalten in Real-time systems Springer US, 1989 58(2022), 4 vom: 19. Feb., Seite 456-508 (DE-627)130955892 (DE-600)1064543-3 (DE-576)025100394 0922-6443 nnns volume:58 year:2022 number:4 day:19 month:02 pages:456-508 https://doi.org/10.1007/s11241-022-09377-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_4036 AR 58 2022 4 19 02 456-508 |
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10.1007/s11241-022-09377-8 doi (DE-627)OLC2080038648 (DE-He213)s11241-022-09377-8-p DE-627 ger DE-627 rakwb eng 004 VZ Davis, Robert I. verfasserin (orcid)0000-0002-5772-0928 aut A framework for multi-core schedulability analysis accounting for resource stress and sensitivity 2022 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2022 Abstract Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on resources and how much it is sensitive to such resource stress. This model facilitates a separation of concerns, thus retaining the advantages of the traditional two-step approach to timing verification (i.e. timing analysis followed by schedulability analysis). Response time analysis is derived for the MRSS task model, providing efficient context-dependent and context independent schedulability tests for both fixed priority preemptive and fixed priority non-preemptive scheduling. Dominance relations are derived between the tests, along with complexity results, and proofs of optimal priority assignment policies. The MRSS task model is underpinned by a proof-of-concept industrial case study. The problem of task allocation is considered in the context of the MRSS task model, with Simulated Annealing shown to provide an effective solution. Schedulability analysis Multi-core Cross-core contention Interference Partitioned scheduling Fixed priority preemptive scheduling Fixed priority non-preemptive scheduling Griffin, David aut Bate, Iain aut Enthalten in Real-time systems Springer US, 1989 58(2022), 4 vom: 19. Feb., Seite 456-508 (DE-627)130955892 (DE-600)1064543-3 (DE-576)025100394 0922-6443 nnns volume:58 year:2022 number:4 day:19 month:02 pages:456-508 https://doi.org/10.1007/s11241-022-09377-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_4036 AR 58 2022 4 19 02 456-508 |
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10.1007/s11241-022-09377-8 doi (DE-627)OLC2080038648 (DE-He213)s11241-022-09377-8-p DE-627 ger DE-627 rakwb eng 004 VZ Davis, Robert I. verfasserin (orcid)0000-0002-5772-0928 aut A framework for multi-core schedulability analysis accounting for resource stress and sensitivity 2022 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2022 Abstract Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on resources and how much it is sensitive to such resource stress. This model facilitates a separation of concerns, thus retaining the advantages of the traditional two-step approach to timing verification (i.e. timing analysis followed by schedulability analysis). Response time analysis is derived for the MRSS task model, providing efficient context-dependent and context independent schedulability tests for both fixed priority preemptive and fixed priority non-preemptive scheduling. Dominance relations are derived between the tests, along with complexity results, and proofs of optimal priority assignment policies. The MRSS task model is underpinned by a proof-of-concept industrial case study. The problem of task allocation is considered in the context of the MRSS task model, with Simulated Annealing shown to provide an effective solution. Schedulability analysis Multi-core Cross-core contention Interference Partitioned scheduling Fixed priority preemptive scheduling Fixed priority non-preemptive scheduling Griffin, David aut Bate, Iain aut Enthalten in Real-time systems Springer US, 1989 58(2022), 4 vom: 19. Feb., Seite 456-508 (DE-627)130955892 (DE-600)1064543-3 (DE-576)025100394 0922-6443 nnns volume:58 year:2022 number:4 day:19 month:02 pages:456-508 https://doi.org/10.1007/s11241-022-09377-8 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_4036 AR 58 2022 4 19 02 456-508 |
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Abstract Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on resources and how much it is sensitive to such resource stress. This model facilitates a separation of concerns, thus retaining the advantages of the traditional two-step approach to timing verification (i.e. timing analysis followed by schedulability analysis). Response time analysis is derived for the MRSS task model, providing efficient context-dependent and context independent schedulability tests for both fixed priority preemptive and fixed priority non-preemptive scheduling. Dominance relations are derived between the tests, along with complexity results, and proofs of optimal priority assignment policies. The MRSS task model is underpinned by a proof-of-concept industrial case study. The problem of task allocation is considered in the context of the MRSS task model, with Simulated Annealing shown to provide an effective solution. © The Author(s) 2022 |
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Abstract Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on resources and how much it is sensitive to such resource stress. This model facilitates a separation of concerns, thus retaining the advantages of the traditional two-step approach to timing verification (i.e. timing analysis followed by schedulability analysis). Response time analysis is derived for the MRSS task model, providing efficient context-dependent and context independent schedulability tests for both fixed priority preemptive and fixed priority non-preemptive scheduling. Dominance relations are derived between the tests, along with complexity results, and proofs of optimal priority assignment policies. The MRSS task model is underpinned by a proof-of-concept industrial case study. The problem of task allocation is considered in the context of the MRSS task model, with Simulated Annealing shown to provide an effective solution. © The Author(s) 2022 |
| abstract_unstemmed |
Abstract Timing verification of multi-core systems is complicated by contention for shared hardware resources between co-running tasks on different cores. This paper introduces the Multi-core Resource Stress and Sensitivity (MRSS) task model that characterizes how much stress each task places on resources and how much it is sensitive to such resource stress. This model facilitates a separation of concerns, thus retaining the advantages of the traditional two-step approach to timing verification (i.e. timing analysis followed by schedulability analysis). Response time analysis is derived for the MRSS task model, providing efficient context-dependent and context independent schedulability tests for both fixed priority preemptive and fixed priority non-preemptive scheduling. Dominance relations are derived between the tests, along with complexity results, and proofs of optimal priority assignment policies. The MRSS task model is underpinned by a proof-of-concept industrial case study. The problem of task allocation is considered in the context of the MRSS task model, with Simulated Annealing shown to provide an effective solution. © The Author(s) 2022 |
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A framework for multi-core schedulability analysis accounting for resource stress and sensitivity |
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Griffin, David Bate, Iain |
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