TaskMUSTER: a comprehensive analysis of task parameters for mixed criticality automotive systems
Abstract Automotive computing platforms are becoming complex and steadily being transformed into mixed criticality systems (MCS) with connectivity to the user, infrastructure and other vehicles. Due to the safety critical and real time nature of such systems, this transition emphasizes careful selec...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Sukumaran Nair, Arun [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2021 |
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| Schlagwörter: |
Uni-core mixed criticality systems multi-core mixed criticality systems |
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| Anmerkung: |
© Indian Academy of Sciences 2021 |
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| Übergeordnetes Werk: |
Enthalten in: Sādhāna - Bangalore : Acad., 1978, 47(2021), 1 vom: 31. Dez. |
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| Übergeordnetes Werk: |
volume:47 ; year:2021 ; number:1 ; day:31 ; month:12 |
| Links: |
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| DOI / URN: |
10.1007/s12046-021-01778-y |
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| Katalog-ID: |
SPR045859256 |
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| 520 | |a Abstract Automotive computing platforms are becoming complex and steadily being transformed into mixed criticality systems (MCS) with connectivity to the user, infrastructure and other vehicles. Due to the safety critical and real time nature of such systems, this transition emphasizes careful selection of task models, task scheduling mechanisms and software development practices to ensure predictability. Though there exists a wealth of research results on MCS, often the non-uniform descriptions and non-comprehensive nature of task parameters become hindrances to the designers and researchers, thus limiting their wider applicability. In this context, we carry out a comprehensive analysis of task parameters for MCS and propose a task parameter aggregator called TaskMUSTER with focus on automotive domain, specifically on the controlling domain software applications like power steering, brake systems and power train. TaskMSUTER aims to provide a unified view of various task model parameters in terms of important attributes related to resource & communication, energy, fault-tolerance, mode change, OS overheads and parallel processing. This work also provides Backus-Naur form grammar and railroad diagram of TaskMUSTER. The usability analysis of TaskMUSTER and comparisons with well-known task model propositions are carried out using an automotive wake-up controller task set. The results justify the suitability of TaskMUSTER for designing safety certifiable automotive MCS. Overall, TaskMUSTER acts as a comprehensive and design friendly handbook for researchers and designers in the mixed criticality automotive controlling domain. | ||
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10.1007/s12046-021-01778-y doi (DE-627)SPR045859256 (SPR)s12046-021-01778-y-e DE-627 ger DE-627 rakwb eng Sukumaran Nair, Arun verfasserin (orcid)0000-0001-9669-514X aut TaskMUSTER: a comprehensive analysis of task parameters for mixed criticality automotive systems 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Academy of Sciences 2021 Abstract Automotive computing platforms are becoming complex and steadily being transformed into mixed criticality systems (MCS) with connectivity to the user, infrastructure and other vehicles. Due to the safety critical and real time nature of such systems, this transition emphasizes careful selection of task models, task scheduling mechanisms and software development practices to ensure predictability. Though there exists a wealth of research results on MCS, often the non-uniform descriptions and non-comprehensive nature of task parameters become hindrances to the designers and researchers, thus limiting their wider applicability. In this context, we carry out a comprehensive analysis of task parameters for MCS and propose a task parameter aggregator called TaskMUSTER with focus on automotive domain, specifically on the controlling domain software applications like power steering, brake systems and power train. TaskMSUTER aims to provide a unified view of various task model parameters in terms of important attributes related to resource & communication, energy, fault-tolerance, mode change, OS overheads and parallel processing. This work also provides Backus-Naur form grammar and railroad diagram of TaskMUSTER. The usability analysis of TaskMUSTER and comparisons with well-known task model propositions are carried out using an automotive wake-up controller task set. The results justify the suitability of TaskMUSTER for designing safety certifiable automotive MCS. Overall, TaskMUSTER acts as a comprehensive and design friendly handbook for researchers and designers in the mixed criticality automotive controlling domain. Uni-core mixed criticality systems (dpeaa)DE-He213 multi-core mixed criticality systems (dpeaa)DE-He213 task model for mixed criticality systems (dpeaa)DE-He213 mixed criticality scheduling (dpeaa)DE-He213 Colaco, Louella Mesquita aut Raveendran, Biju aut Punnekkat, Sasikumar aut Enthalten in Sādhāna Bangalore : Acad., 1978 47(2021), 1 vom: 31. Dez. (DE-627)359574963 (DE-600)2097680-X 0973-7677 nnns volume:47 year:2021 number:1 day:31 month:12 https://dx.doi.org/10.1007/s12046-021-01778-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 47 2021 1 31 12 |
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10.1007/s12046-021-01778-y doi (DE-627)SPR045859256 (SPR)s12046-021-01778-y-e DE-627 ger DE-627 rakwb eng Sukumaran Nair, Arun verfasserin (orcid)0000-0001-9669-514X aut TaskMUSTER: a comprehensive analysis of task parameters for mixed criticality automotive systems 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Academy of Sciences 2021 Abstract Automotive computing platforms are becoming complex and steadily being transformed into mixed criticality systems (MCS) with connectivity to the user, infrastructure and other vehicles. Due to the safety critical and real time nature of such systems, this transition emphasizes careful selection of task models, task scheduling mechanisms and software development practices to ensure predictability. Though there exists a wealth of research results on MCS, often the non-uniform descriptions and non-comprehensive nature of task parameters become hindrances to the designers and researchers, thus limiting their wider applicability. In this context, we carry out a comprehensive analysis of task parameters for MCS and propose a task parameter aggregator called TaskMUSTER with focus on automotive domain, specifically on the controlling domain software applications like power steering, brake systems and power train. TaskMSUTER aims to provide a unified view of various task model parameters in terms of important attributes related to resource & communication, energy, fault-tolerance, mode change, OS overheads and parallel processing. This work also provides Backus-Naur form grammar and railroad diagram of TaskMUSTER. The usability analysis of TaskMUSTER and comparisons with well-known task model propositions are carried out using an automotive wake-up controller task set. The results justify the suitability of TaskMUSTER for designing safety certifiable automotive MCS. Overall, TaskMUSTER acts as a comprehensive and design friendly handbook for researchers and designers in the mixed criticality automotive controlling domain. Uni-core mixed criticality systems (dpeaa)DE-He213 multi-core mixed criticality systems (dpeaa)DE-He213 task model for mixed criticality systems (dpeaa)DE-He213 mixed criticality scheduling (dpeaa)DE-He213 Colaco, Louella Mesquita aut Raveendran, Biju aut Punnekkat, Sasikumar aut Enthalten in Sādhāna Bangalore : Acad., 1978 47(2021), 1 vom: 31. Dez. (DE-627)359574963 (DE-600)2097680-X 0973-7677 nnns volume:47 year:2021 number:1 day:31 month:12 https://dx.doi.org/10.1007/s12046-021-01778-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 47 2021 1 31 12 |
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10.1007/s12046-021-01778-y doi (DE-627)SPR045859256 (SPR)s12046-021-01778-y-e DE-627 ger DE-627 rakwb eng Sukumaran Nair, Arun verfasserin (orcid)0000-0001-9669-514X aut TaskMUSTER: a comprehensive analysis of task parameters for mixed criticality automotive systems 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Academy of Sciences 2021 Abstract Automotive computing platforms are becoming complex and steadily being transformed into mixed criticality systems (MCS) with connectivity to the user, infrastructure and other vehicles. Due to the safety critical and real time nature of such systems, this transition emphasizes careful selection of task models, task scheduling mechanisms and software development practices to ensure predictability. Though there exists a wealth of research results on MCS, often the non-uniform descriptions and non-comprehensive nature of task parameters become hindrances to the designers and researchers, thus limiting their wider applicability. In this context, we carry out a comprehensive analysis of task parameters for MCS and propose a task parameter aggregator called TaskMUSTER with focus on automotive domain, specifically on the controlling domain software applications like power steering, brake systems and power train. TaskMSUTER aims to provide a unified view of various task model parameters in terms of important attributes related to resource & communication, energy, fault-tolerance, mode change, OS overheads and parallel processing. This work also provides Backus-Naur form grammar and railroad diagram of TaskMUSTER. The usability analysis of TaskMUSTER and comparisons with well-known task model propositions are carried out using an automotive wake-up controller task set. The results justify the suitability of TaskMUSTER for designing safety certifiable automotive MCS. Overall, TaskMUSTER acts as a comprehensive and design friendly handbook for researchers and designers in the mixed criticality automotive controlling domain. Uni-core mixed criticality systems (dpeaa)DE-He213 multi-core mixed criticality systems (dpeaa)DE-He213 task model for mixed criticality systems (dpeaa)DE-He213 mixed criticality scheduling (dpeaa)DE-He213 Colaco, Louella Mesquita aut Raveendran, Biju aut Punnekkat, Sasikumar aut Enthalten in Sādhāna Bangalore : Acad., 1978 47(2021), 1 vom: 31. Dez. (DE-627)359574963 (DE-600)2097680-X 0973-7677 nnns volume:47 year:2021 number:1 day:31 month:12 https://dx.doi.org/10.1007/s12046-021-01778-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 47 2021 1 31 12 |
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10.1007/s12046-021-01778-y doi (DE-627)SPR045859256 (SPR)s12046-021-01778-y-e DE-627 ger DE-627 rakwb eng Sukumaran Nair, Arun verfasserin (orcid)0000-0001-9669-514X aut TaskMUSTER: a comprehensive analysis of task parameters for mixed criticality automotive systems 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Academy of Sciences 2021 Abstract Automotive computing platforms are becoming complex and steadily being transformed into mixed criticality systems (MCS) with connectivity to the user, infrastructure and other vehicles. Due to the safety critical and real time nature of such systems, this transition emphasizes careful selection of task models, task scheduling mechanisms and software development practices to ensure predictability. Though there exists a wealth of research results on MCS, often the non-uniform descriptions and non-comprehensive nature of task parameters become hindrances to the designers and researchers, thus limiting their wider applicability. In this context, we carry out a comprehensive analysis of task parameters for MCS and propose a task parameter aggregator called TaskMUSTER with focus on automotive domain, specifically on the controlling domain software applications like power steering, brake systems and power train. TaskMSUTER aims to provide a unified view of various task model parameters in terms of important attributes related to resource & communication, energy, fault-tolerance, mode change, OS overheads and parallel processing. This work also provides Backus-Naur form grammar and railroad diagram of TaskMUSTER. The usability analysis of TaskMUSTER and comparisons with well-known task model propositions are carried out using an automotive wake-up controller task set. The results justify the suitability of TaskMUSTER for designing safety certifiable automotive MCS. Overall, TaskMUSTER acts as a comprehensive and design friendly handbook for researchers and designers in the mixed criticality automotive controlling domain. Uni-core mixed criticality systems (dpeaa)DE-He213 multi-core mixed criticality systems (dpeaa)DE-He213 task model for mixed criticality systems (dpeaa)DE-He213 mixed criticality scheduling (dpeaa)DE-He213 Colaco, Louella Mesquita aut Raveendran, Biju aut Punnekkat, Sasikumar aut Enthalten in Sādhāna Bangalore : Acad., 1978 47(2021), 1 vom: 31. Dez. (DE-627)359574963 (DE-600)2097680-X 0973-7677 nnns volume:47 year:2021 number:1 day:31 month:12 https://dx.doi.org/10.1007/s12046-021-01778-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 47 2021 1 31 12 |
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10.1007/s12046-021-01778-y doi (DE-627)SPR045859256 (SPR)s12046-021-01778-y-e DE-627 ger DE-627 rakwb eng Sukumaran Nair, Arun verfasserin (orcid)0000-0001-9669-514X aut TaskMUSTER: a comprehensive analysis of task parameters for mixed criticality automotive systems 2021 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier © Indian Academy of Sciences 2021 Abstract Automotive computing platforms are becoming complex and steadily being transformed into mixed criticality systems (MCS) with connectivity to the user, infrastructure and other vehicles. Due to the safety critical and real time nature of such systems, this transition emphasizes careful selection of task models, task scheduling mechanisms and software development practices to ensure predictability. Though there exists a wealth of research results on MCS, often the non-uniform descriptions and non-comprehensive nature of task parameters become hindrances to the designers and researchers, thus limiting their wider applicability. In this context, we carry out a comprehensive analysis of task parameters for MCS and propose a task parameter aggregator called TaskMUSTER with focus on automotive domain, specifically on the controlling domain software applications like power steering, brake systems and power train. TaskMSUTER aims to provide a unified view of various task model parameters in terms of important attributes related to resource & communication, energy, fault-tolerance, mode change, OS overheads and parallel processing. This work also provides Backus-Naur form grammar and railroad diagram of TaskMUSTER. The usability analysis of TaskMUSTER and comparisons with well-known task model propositions are carried out using an automotive wake-up controller task set. The results justify the suitability of TaskMUSTER for designing safety certifiable automotive MCS. Overall, TaskMUSTER acts as a comprehensive and design friendly handbook for researchers and designers in the mixed criticality automotive controlling domain. Uni-core mixed criticality systems (dpeaa)DE-He213 multi-core mixed criticality systems (dpeaa)DE-He213 task model for mixed criticality systems (dpeaa)DE-He213 mixed criticality scheduling (dpeaa)DE-He213 Colaco, Louella Mesquita aut Raveendran, Biju aut Punnekkat, Sasikumar aut Enthalten in Sādhāna Bangalore : Acad., 1978 47(2021), 1 vom: 31. Dez. (DE-627)359574963 (DE-600)2097680-X 0973-7677 nnns volume:47 year:2021 number:1 day:31 month:12 https://dx.doi.org/10.1007/s12046-021-01778-y lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_SPRINGER GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_32 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_105 GBV_ILN_110 GBV_ILN_120 GBV_ILN_138 GBV_ILN_150 GBV_ILN_151 GBV_ILN_152 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_187 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_250 GBV_ILN_281 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_636 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2004 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2007 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2026 GBV_ILN_2027 GBV_ILN_2031 GBV_ILN_2034 GBV_ILN_2037 GBV_ILN_2038 GBV_ILN_2039 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2049 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2059 GBV_ILN_2061 GBV_ILN_2064 GBV_ILN_2065 GBV_ILN_2068 GBV_ILN_2088 GBV_ILN_2093 GBV_ILN_2106 GBV_ILN_2107 GBV_ILN_2108 GBV_ILN_2110 GBV_ILN_2111 GBV_ILN_2112 GBV_ILN_2113 GBV_ILN_2118 GBV_ILN_2119 GBV_ILN_2122 GBV_ILN_2129 GBV_ILN_2143 GBV_ILN_2144 GBV_ILN_2147 GBV_ILN_2148 GBV_ILN_2152 GBV_ILN_2153 GBV_ILN_2188 GBV_ILN_2190 GBV_ILN_2232 GBV_ILN_2336 GBV_ILN_2446 GBV_ILN_2470 GBV_ILN_2472 GBV_ILN_2507 GBV_ILN_2522 GBV_ILN_2548 GBV_ILN_4012 GBV_ILN_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4242 GBV_ILN_4246 GBV_ILN_4249 GBV_ILN_4251 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4326 GBV_ILN_4328 GBV_ILN_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4393 GBV_ILN_4700 AR 47 2021 1 31 12 |
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Sukumaran Nair, Arun @@aut@@ Colaco, Louella Mesquita @@aut@@ Raveendran, Biju @@aut@@ Punnekkat, Sasikumar @@aut@@ |
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Sukumaran Nair, Arun |
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TaskMUSTER: a comprehensive analysis of task parameters for mixed criticality automotive systems Uni-core mixed criticality systems (dpeaa)DE-He213 multi-core mixed criticality systems (dpeaa)DE-He213 task model for mixed criticality systems (dpeaa)DE-He213 mixed criticality scheduling (dpeaa)DE-He213 |
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taskmuster: a comprehensive analysis of task parameters for mixed criticality automotive systems |
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TaskMUSTER: a comprehensive analysis of task parameters for mixed criticality automotive systems |
| abstract |
Abstract Automotive computing platforms are becoming complex and steadily being transformed into mixed criticality systems (MCS) with connectivity to the user, infrastructure and other vehicles. Due to the safety critical and real time nature of such systems, this transition emphasizes careful selection of task models, task scheduling mechanisms and software development practices to ensure predictability. Though there exists a wealth of research results on MCS, often the non-uniform descriptions and non-comprehensive nature of task parameters become hindrances to the designers and researchers, thus limiting their wider applicability. In this context, we carry out a comprehensive analysis of task parameters for MCS and propose a task parameter aggregator called TaskMUSTER with focus on automotive domain, specifically on the controlling domain software applications like power steering, brake systems and power train. TaskMSUTER aims to provide a unified view of various task model parameters in terms of important attributes related to resource & communication, energy, fault-tolerance, mode change, OS overheads and parallel processing. This work also provides Backus-Naur form grammar and railroad diagram of TaskMUSTER. The usability analysis of TaskMUSTER and comparisons with well-known task model propositions are carried out using an automotive wake-up controller task set. The results justify the suitability of TaskMUSTER for designing safety certifiable automotive MCS. Overall, TaskMUSTER acts as a comprehensive and design friendly handbook for researchers and designers in the mixed criticality automotive controlling domain. © Indian Academy of Sciences 2021 |
| abstractGer |
Abstract Automotive computing platforms are becoming complex and steadily being transformed into mixed criticality systems (MCS) with connectivity to the user, infrastructure and other vehicles. Due to the safety critical and real time nature of such systems, this transition emphasizes careful selection of task models, task scheduling mechanisms and software development practices to ensure predictability. Though there exists a wealth of research results on MCS, often the non-uniform descriptions and non-comprehensive nature of task parameters become hindrances to the designers and researchers, thus limiting their wider applicability. In this context, we carry out a comprehensive analysis of task parameters for MCS and propose a task parameter aggregator called TaskMUSTER with focus on automotive domain, specifically on the controlling domain software applications like power steering, brake systems and power train. TaskMSUTER aims to provide a unified view of various task model parameters in terms of important attributes related to resource & communication, energy, fault-tolerance, mode change, OS overheads and parallel processing. This work also provides Backus-Naur form grammar and railroad diagram of TaskMUSTER. The usability analysis of TaskMUSTER and comparisons with well-known task model propositions are carried out using an automotive wake-up controller task set. The results justify the suitability of TaskMUSTER for designing safety certifiable automotive MCS. Overall, TaskMUSTER acts as a comprehensive and design friendly handbook for researchers and designers in the mixed criticality automotive controlling domain. © Indian Academy of Sciences 2021 |
| abstract_unstemmed |
Abstract Automotive computing platforms are becoming complex and steadily being transformed into mixed criticality systems (MCS) with connectivity to the user, infrastructure and other vehicles. Due to the safety critical and real time nature of such systems, this transition emphasizes careful selection of task models, task scheduling mechanisms and software development practices to ensure predictability. Though there exists a wealth of research results on MCS, often the non-uniform descriptions and non-comprehensive nature of task parameters become hindrances to the designers and researchers, thus limiting their wider applicability. In this context, we carry out a comprehensive analysis of task parameters for MCS and propose a task parameter aggregator called TaskMUSTER with focus on automotive domain, specifically on the controlling domain software applications like power steering, brake systems and power train. TaskMSUTER aims to provide a unified view of various task model parameters in terms of important attributes related to resource & communication, energy, fault-tolerance, mode change, OS overheads and parallel processing. This work also provides Backus-Naur form grammar and railroad diagram of TaskMUSTER. The usability analysis of TaskMUSTER and comparisons with well-known task model propositions are carried out using an automotive wake-up controller task set. The results justify the suitability of TaskMUSTER for designing safety certifiable automotive MCS. Overall, TaskMUSTER acts as a comprehensive and design friendly handbook for researchers and designers in the mixed criticality automotive controlling domain. © Indian Academy of Sciences 2021 |
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TaskMUSTER: a comprehensive analysis of task parameters for mixed criticality automotive systems |
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https://dx.doi.org/10.1007/s12046-021-01778-y |
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Colaco, Louella Mesquita Raveendran, Biju Punnekkat, Sasikumar |
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Colaco, Louella Mesquita Raveendran, Biju Punnekkat, Sasikumar |
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| doi_str |
10.1007/s12046-021-01778-y |
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2024-07-03T18:45:43.403Z |
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| score |
7.401664 |