Optimal task execution times for periodic tasks using nonlinear constrained optimization

Abstract Designing real-time systems is a challenging task and many conflicting issues arise in the process. Among them, the most fundamental one is the adjustment of appropriate values for task parameters such as task periods, deadlines, and computation times that directly influence the system feas...
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Autor*in:	Min-Allah, Nasro [verfasserIn] Khan, Samee Ullah [verfasserIn] Yongji, Wang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2010

Schlagwörter:	Real-time systems Fixed-priority scheduling Feasibility analysis Nonlinear programming

Übergeordnetes Werk:	Enthalten in: The journal of supercomputing - Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987, 59(2010), 3 vom: 10. Nov., Seite 1120-1138
Übergeordnetes Werk:	volume:59 ; year:2010 ; number:3 ; day:10 ; month:11 ; pages:1120-1138

Links:	Volltext

DOI / URN:	10.1007/s11227-010-0506-z

Katalog-ID:	SPR018004466

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245	1	0	\|a Optimal task execution times for periodic tasks using nonlinear constrained optimization
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520			\|a Abstract Designing real-time systems is a challenging task and many conflicting issues arise in the process. Among them, the most fundamental one is the adjustment of appropriate values for task parameters such as task periods, deadlines, and computation times that directly influence the system feasibility. Task periods and deadlines are generally known at design stage and remains fixed throughout, however, task computation times fluctuates significantly. For a better quality of service or higher system utilization, higher task computation values are required, while this flexibility comes at the price of system infeasibility. To the best of our knowledge, no optimal solution exists for extracting the optimal task computation times in a given range so that the overall system remains feasible under a specific scheduling algorithm. In this paper, we present a generalized bound on the task schedulability defined as a nonlinear inequality hi≤0 in the space of the execution times ci. Based on this bound, the adjustment problem of tasks execution times, which determines the optimum ci for a better system performance while still meeting all temporal requirements, is addressed by solving the standard nonlinear constrained optimization problem. Simulations on synthetic task sets are presented to compare the performance of our work with the most celebrated result, i.e., LL-bound by Liu and Layland in (J. ACM 20(1):40–61, 1973).
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650		4	\|a Fixed-priority scheduling \|7 (dpeaa)DE-He213
650		4	\|a Feasibility analysis \|7 (dpeaa)DE-He213
650		4	\|a Nonlinear programming \|7 (dpeaa)DE-He213
700	1		\|a Khan, Samee Ullah \|e verfasserin \|4 aut
700	1		\|a Yongji, Wang \|e verfasserin \|4 aut
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allfields	10.1007/s11227-010-0506-z doi (DE-627)SPR018004466 (SPR)s11227-010-0506-z-e DE-627 ger DE-627 rakwb eng 004 620 ASE 54.20 bkl Min-Allah, Nasro verfasserin aut Optimal task execution times for periodic tasks using nonlinear constrained optimization 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Designing real-time systems is a challenging task and many conflicting issues arise in the process. Among them, the most fundamental one is the adjustment of appropriate values for task parameters such as task periods, deadlines, and computation times that directly influence the system feasibility. Task periods and deadlines are generally known at design stage and remains fixed throughout, however, task computation times fluctuates significantly. For a better quality of service or higher system utilization, higher task computation values are required, while this flexibility comes at the price of system infeasibility. To the best of our knowledge, no optimal solution exists for extracting the optimal task computation times in a given range so that the overall system remains feasible under a specific scheduling algorithm. In this paper, we present a generalized bound on the task schedulability defined as a nonlinear inequality hi≤0 in the space of the execution times ci. Based on this bound, the adjustment problem of tasks execution times, which determines the optimum ci for a better system performance while still meeting all temporal requirements, is addressed by solving the standard nonlinear constrained optimization problem. Simulations on synthetic task sets are presented to compare the performance of our work with the most celebrated result, i.e., LL-bound by Liu and Layland in (J. ACM 20(1):40–61, 1973). Real-time systems (dpeaa)DE-He213 Fixed-priority scheduling (dpeaa)DE-He213 Feasibility analysis (dpeaa)DE-He213 Nonlinear programming (dpeaa)DE-He213 Khan, Samee Ullah verfasserin aut Yongji, Wang verfasserin aut Enthalten in The journal of supercomputing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 59(2010), 3 vom: 10. Nov., Seite 1120-1138 (DE-627)271350202 (DE-600)1479917-0 1573-0484 nnns volume:59 year:2010 number:3 day:10 month:11 pages:1120-1138 https://dx.doi.org/10.1007/s11227-010-0506-z 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 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_2070 GBV_ILN_2086 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_2116 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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.20 ASE AR 59 2010 3 10 11 1120-1138
spelling	10.1007/s11227-010-0506-z doi (DE-627)SPR018004466 (SPR)s11227-010-0506-z-e DE-627 ger DE-627 rakwb eng 004 620 ASE 54.20 bkl Min-Allah, Nasro verfasserin aut Optimal task execution times for periodic tasks using nonlinear constrained optimization 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Designing real-time systems is a challenging task and many conflicting issues arise in the process. Among them, the most fundamental one is the adjustment of appropriate values for task parameters such as task periods, deadlines, and computation times that directly influence the system feasibility. Task periods and deadlines are generally known at design stage and remains fixed throughout, however, task computation times fluctuates significantly. For a better quality of service or higher system utilization, higher task computation values are required, while this flexibility comes at the price of system infeasibility. To the best of our knowledge, no optimal solution exists for extracting the optimal task computation times in a given range so that the overall system remains feasible under a specific scheduling algorithm. In this paper, we present a generalized bound on the task schedulability defined as a nonlinear inequality hi≤0 in the space of the execution times ci. Based on this bound, the adjustment problem of tasks execution times, which determines the optimum ci for a better system performance while still meeting all temporal requirements, is addressed by solving the standard nonlinear constrained optimization problem. Simulations on synthetic task sets are presented to compare the performance of our work with the most celebrated result, i.e., LL-bound by Liu and Layland in (J. ACM 20(1):40–61, 1973). Real-time systems (dpeaa)DE-He213 Fixed-priority scheduling (dpeaa)DE-He213 Feasibility analysis (dpeaa)DE-He213 Nonlinear programming (dpeaa)DE-He213 Khan, Samee Ullah verfasserin aut Yongji, Wang verfasserin aut Enthalten in The journal of supercomputing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 59(2010), 3 vom: 10. Nov., Seite 1120-1138 (DE-627)271350202 (DE-600)1479917-0 1573-0484 nnns volume:59 year:2010 number:3 day:10 month:11 pages:1120-1138 https://dx.doi.org/10.1007/s11227-010-0506-z 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 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_2070 GBV_ILN_2086 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_2116 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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.20 ASE AR 59 2010 3 10 11 1120-1138
allfields_unstemmed	10.1007/s11227-010-0506-z doi (DE-627)SPR018004466 (SPR)s11227-010-0506-z-e DE-627 ger DE-627 rakwb eng 004 620 ASE 54.20 bkl Min-Allah, Nasro verfasserin aut Optimal task execution times for periodic tasks using nonlinear constrained optimization 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Designing real-time systems is a challenging task and many conflicting issues arise in the process. Among them, the most fundamental one is the adjustment of appropriate values for task parameters such as task periods, deadlines, and computation times that directly influence the system feasibility. Task periods and deadlines are generally known at design stage and remains fixed throughout, however, task computation times fluctuates significantly. For a better quality of service or higher system utilization, higher task computation values are required, while this flexibility comes at the price of system infeasibility. To the best of our knowledge, no optimal solution exists for extracting the optimal task computation times in a given range so that the overall system remains feasible under a specific scheduling algorithm. In this paper, we present a generalized bound on the task schedulability defined as a nonlinear inequality hi≤0 in the space of the execution times ci. Based on this bound, the adjustment problem of tasks execution times, which determines the optimum ci for a better system performance while still meeting all temporal requirements, is addressed by solving the standard nonlinear constrained optimization problem. Simulations on synthetic task sets are presented to compare the performance of our work with the most celebrated result, i.e., LL-bound by Liu and Layland in (J. ACM 20(1):40–61, 1973). Real-time systems (dpeaa)DE-He213 Fixed-priority scheduling (dpeaa)DE-He213 Feasibility analysis (dpeaa)DE-He213 Nonlinear programming (dpeaa)DE-He213 Khan, Samee Ullah verfasserin aut Yongji, Wang verfasserin aut Enthalten in The journal of supercomputing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 59(2010), 3 vom: 10. Nov., Seite 1120-1138 (DE-627)271350202 (DE-600)1479917-0 1573-0484 nnns volume:59 year:2010 number:3 day:10 month:11 pages:1120-1138 https://dx.doi.org/10.1007/s11227-010-0506-z 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 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_2070 GBV_ILN_2086 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_2116 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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.20 ASE AR 59 2010 3 10 11 1120-1138
allfieldsGer	10.1007/s11227-010-0506-z doi (DE-627)SPR018004466 (SPR)s11227-010-0506-z-e DE-627 ger DE-627 rakwb eng 004 620 ASE 54.20 bkl Min-Allah, Nasro verfasserin aut Optimal task execution times for periodic tasks using nonlinear constrained optimization 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Designing real-time systems is a challenging task and many conflicting issues arise in the process. Among them, the most fundamental one is the adjustment of appropriate values for task parameters such as task periods, deadlines, and computation times that directly influence the system feasibility. Task periods and deadlines are generally known at design stage and remains fixed throughout, however, task computation times fluctuates significantly. For a better quality of service or higher system utilization, higher task computation values are required, while this flexibility comes at the price of system infeasibility. To the best of our knowledge, no optimal solution exists for extracting the optimal task computation times in a given range so that the overall system remains feasible under a specific scheduling algorithm. In this paper, we present a generalized bound on the task schedulability defined as a nonlinear inequality hi≤0 in the space of the execution times ci. Based on this bound, the adjustment problem of tasks execution times, which determines the optimum ci for a better system performance while still meeting all temporal requirements, is addressed by solving the standard nonlinear constrained optimization problem. Simulations on synthetic task sets are presented to compare the performance of our work with the most celebrated result, i.e., LL-bound by Liu and Layland in (J. ACM 20(1):40–61, 1973). Real-time systems (dpeaa)DE-He213 Fixed-priority scheduling (dpeaa)DE-He213 Feasibility analysis (dpeaa)DE-He213 Nonlinear programming (dpeaa)DE-He213 Khan, Samee Ullah verfasserin aut Yongji, Wang verfasserin aut Enthalten in The journal of supercomputing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 59(2010), 3 vom: 10. Nov., Seite 1120-1138 (DE-627)271350202 (DE-600)1479917-0 1573-0484 nnns volume:59 year:2010 number:3 day:10 month:11 pages:1120-1138 https://dx.doi.org/10.1007/s11227-010-0506-z 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 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_2070 GBV_ILN_2086 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_2116 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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.20 ASE AR 59 2010 3 10 11 1120-1138
allfieldsSound	10.1007/s11227-010-0506-z doi (DE-627)SPR018004466 (SPR)s11227-010-0506-z-e DE-627 ger DE-627 rakwb eng 004 620 ASE 54.20 bkl Min-Allah, Nasro verfasserin aut Optimal task execution times for periodic tasks using nonlinear constrained optimization 2010 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Abstract Designing real-time systems is a challenging task and many conflicting issues arise in the process. Among them, the most fundamental one is the adjustment of appropriate values for task parameters such as task periods, deadlines, and computation times that directly influence the system feasibility. Task periods and deadlines are generally known at design stage and remains fixed throughout, however, task computation times fluctuates significantly. For a better quality of service or higher system utilization, higher task computation values are required, while this flexibility comes at the price of system infeasibility. To the best of our knowledge, no optimal solution exists for extracting the optimal task computation times in a given range so that the overall system remains feasible under a specific scheduling algorithm. In this paper, we present a generalized bound on the task schedulability defined as a nonlinear inequality hi≤0 in the space of the execution times ci. Based on this bound, the adjustment problem of tasks execution times, which determines the optimum ci for a better system performance while still meeting all temporal requirements, is addressed by solving the standard nonlinear constrained optimization problem. Simulations on synthetic task sets are presented to compare the performance of our work with the most celebrated result, i.e., LL-bound by Liu and Layland in (J. ACM 20(1):40–61, 1973). Real-time systems (dpeaa)DE-He213 Fixed-priority scheduling (dpeaa)DE-He213 Feasibility analysis (dpeaa)DE-He213 Nonlinear programming (dpeaa)DE-He213 Khan, Samee Ullah verfasserin aut Yongji, Wang verfasserin aut Enthalten in The journal of supercomputing Dordrecht [u.a.] : Springer Science + Business Media B.V, 1987 59(2010), 3 vom: 10. Nov., Seite 1120-1138 (DE-627)271350202 (DE-600)1479917-0 1573-0484 nnns volume:59 year:2010 number:3 day:10 month:11 pages:1120-1138 https://dx.doi.org/10.1007/s11227-010-0506-z 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_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_90 GBV_ILN_95 GBV_ILN_100 GBV_ILN_101 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_2070 GBV_ILN_2086 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_2116 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_4035 GBV_ILN_4037 GBV_ILN_4046 GBV_ILN_4112 GBV_ILN_4125 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_4333 GBV_ILN_4334 GBV_ILN_4335 GBV_ILN_4336 GBV_ILN_4338 GBV_ILN_4393 GBV_ILN_4700 54.20 ASE AR 59 2010 3 10 11 1120-1138
language	English
source	Enthalten in The journal of supercomputing 59(2010), 3 vom: 10. Nov., Seite 1120-1138 volume:59 year:2010 number:3 day:10 month:11 pages:1120-1138
sourceStr	Enthalten in The journal of supercomputing 59(2010), 3 vom: 10. Nov., Seite 1120-1138 volume:59 year:2010 number:3 day:10 month:11 pages:1120-1138
format_phy_str_mv	Article
institution	findex.gbv.de
topic_facet	Real-time systems Fixed-priority scheduling Feasibility analysis Nonlinear programming
dewey-raw	004
isfreeaccess_bool	false
container_title	The journal of supercomputing
authorswithroles_txt_mv	Min-Allah, Nasro @@aut@@ Khan, Samee Ullah @@aut@@ Yongji, Wang @@aut@@
publishDateDaySort_date	2010-11-10T00:00:00Z
hierarchy_top_id	271350202
dewey-sort	14
id	SPR018004466
language_de	englisch
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author	Min-Allah, Nasro
spellingShingle	Min-Allah, Nasro ddc 004 bkl 54.20 misc Real-time systems misc Fixed-priority scheduling misc Feasibility analysis misc Nonlinear programming Optimal task execution times for periodic tasks using nonlinear constrained optimization
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topic_title	004 620 ASE 54.20 bkl Optimal task execution times for periodic tasks using nonlinear constrained optimization Real-time systems (dpeaa)DE-He213 Fixed-priority scheduling (dpeaa)DE-He213 Feasibility analysis (dpeaa)DE-He213 Nonlinear programming (dpeaa)DE-He213
topic	ddc 004 bkl 54.20 misc Real-time systems misc Fixed-priority scheduling misc Feasibility analysis misc Nonlinear programming
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title	Optimal task execution times for periodic tasks using nonlinear constrained optimization
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title_full	Optimal task execution times for periodic tasks using nonlinear constrained optimization
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title_sort	optimal task execution times for periodic tasks using nonlinear constrained optimization
title_auth	Optimal task execution times for periodic tasks using nonlinear constrained optimization
abstract	Abstract Designing real-time systems is a challenging task and many conflicting issues arise in the process. Among them, the most fundamental one is the adjustment of appropriate values for task parameters such as task periods, deadlines, and computation times that directly influence the system feasibility. Task periods and deadlines are generally known at design stage and remains fixed throughout, however, task computation times fluctuates significantly. For a better quality of service or higher system utilization, higher task computation values are required, while this flexibility comes at the price of system infeasibility. To the best of our knowledge, no optimal solution exists for extracting the optimal task computation times in a given range so that the overall system remains feasible under a specific scheduling algorithm. In this paper, we present a generalized bound on the task schedulability defined as a nonlinear inequality hi≤0 in the space of the execution times ci. Based on this bound, the adjustment problem of tasks execution times, which determines the optimum ci for a better system performance while still meeting all temporal requirements, is addressed by solving the standard nonlinear constrained optimization problem. Simulations on synthetic task sets are presented to compare the performance of our work with the most celebrated result, i.e., LL-bound by Liu and Layland in (J. ACM 20(1):40–61, 1973).
abstractGer	Abstract Designing real-time systems is a challenging task and many conflicting issues arise in the process. Among them, the most fundamental one is the adjustment of appropriate values for task parameters such as task periods, deadlines, and computation times that directly influence the system feasibility. Task periods and deadlines are generally known at design stage and remains fixed throughout, however, task computation times fluctuates significantly. For a better quality of service or higher system utilization, higher task computation values are required, while this flexibility comes at the price of system infeasibility. To the best of our knowledge, no optimal solution exists for extracting the optimal task computation times in a given range so that the overall system remains feasible under a specific scheduling algorithm. In this paper, we present a generalized bound on the task schedulability defined as a nonlinear inequality hi≤0 in the space of the execution times ci. Based on this bound, the adjustment problem of tasks execution times, which determines the optimum ci for a better system performance while still meeting all temporal requirements, is addressed by solving the standard nonlinear constrained optimization problem. Simulations on synthetic task sets are presented to compare the performance of our work with the most celebrated result, i.e., LL-bound by Liu and Layland in (J. ACM 20(1):40–61, 1973).
abstract_unstemmed	Abstract Designing real-time systems is a challenging task and many conflicting issues arise in the process. Among them, the most fundamental one is the adjustment of appropriate values for task parameters such as task periods, deadlines, and computation times that directly influence the system feasibility. Task periods and deadlines are generally known at design stage and remains fixed throughout, however, task computation times fluctuates significantly. For a better quality of service or higher system utilization, higher task computation values are required, while this flexibility comes at the price of system infeasibility. To the best of our knowledge, no optimal solution exists for extracting the optimal task computation times in a given range so that the overall system remains feasible under a specific scheduling algorithm. In this paper, we present a generalized bound on the task schedulability defined as a nonlinear inequality hi≤0 in the space of the execution times ci. Based on this bound, the adjustment problem of tasks execution times, which determines the optimum ci for a better system performance while still meeting all temporal requirements, is addressed by solving the standard nonlinear constrained optimization problem. Simulations on synthetic task sets are presented to compare the performance of our work with the most celebrated result, i.e., LL-bound by Liu and Layland in (J. ACM 20(1):40–61, 1973).
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title_short	Optimal task execution times for periodic tasks using nonlinear constrained optimization
url	https://dx.doi.org/10.1007/s11227-010-0506-z
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Optimal task execution times for periodic tasks using nonlinear constrained optimization

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