A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud

The moldable parallel task (MPT) is a kind of parallel task that their sub-tasks hold the resources exclusively, which has been widely used in different areas. Our paper focuses on the scheduling of moldable tasks when every sub-task supports time-slice. The time-slice is a consecutive time that the...
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Autor*in:	Jianmin Li [verfasserIn] Ying Zhong [verfasserIn] Xin Zhang [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2019

Schlagwörter:	Moldable parallel task speedup parallelism scheduling method

Übergeordnetes Werk:	In: IEEE Access - IEEE, 2014, 7(2019), Seite 86145-86156
Übergeordnetes Werk:	volume:7 ; year:2019 ; pages:86145-86156

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1109/ACCESS.2019.2925429

Katalog-ID:	DOAJ056532474

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allfields	10.1109/ACCESS.2019.2925429 doi (DE-627)DOAJ056532474 (DE-599)DOAJ0f278123a5854d559d493d60a3ac7f2f DE-627 ger DE-627 rakwb eng TK1-9971 Jianmin Li verfasserin aut A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The moldable parallel task (MPT) is a kind of parallel task that their sub-tasks hold the resources exclusively, which has been widely used in different areas. Our paper focuses on the scheduling of moldable tasks when every sub-task supports time-slice. The time-slice is a consecutive time that the sub-task holds the resources exclusively. After every time-slice, the sub-task can be canceled, suspended, or continued. We give the model of MPTs and propose a scheduling method for MPTs: MC (a heuristic scheduling method supporting time-slice model on the cloud). The simulation results show that, even under a forecast accuracy of system load under 90% and 95%, MC reduces average waiting time and average execution time; at the same time, MC has a lower value in the percentages of unfinished tasks. Moldable parallel task speedup parallelism scheduling method Electrical engineering. Electronics. Nuclear engineering Ying Zhong verfasserin aut Xin Zhang verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 86145-86156 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:86145-86156 https://doi.org/10.1109/ACCESS.2019.2925429 kostenfrei https://doaj.org/article/0f278123a5854d559d493d60a3ac7f2f kostenfrei https://ieeexplore.ieee.org/document/8746995/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 86145-86156
spelling	10.1109/ACCESS.2019.2925429 doi (DE-627)DOAJ056532474 (DE-599)DOAJ0f278123a5854d559d493d60a3ac7f2f DE-627 ger DE-627 rakwb eng TK1-9971 Jianmin Li verfasserin aut A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The moldable parallel task (MPT) is a kind of parallel task that their sub-tasks hold the resources exclusively, which has been widely used in different areas. Our paper focuses on the scheduling of moldable tasks when every sub-task supports time-slice. The time-slice is a consecutive time that the sub-task holds the resources exclusively. After every time-slice, the sub-task can be canceled, suspended, or continued. We give the model of MPTs and propose a scheduling method for MPTs: MC (a heuristic scheduling method supporting time-slice model on the cloud). The simulation results show that, even under a forecast accuracy of system load under 90% and 95%, MC reduces average waiting time and average execution time; at the same time, MC has a lower value in the percentages of unfinished tasks. Moldable parallel task speedup parallelism scheduling method Electrical engineering. Electronics. Nuclear engineering Ying Zhong verfasserin aut Xin Zhang verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 86145-86156 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:86145-86156 https://doi.org/10.1109/ACCESS.2019.2925429 kostenfrei https://doaj.org/article/0f278123a5854d559d493d60a3ac7f2f kostenfrei https://ieeexplore.ieee.org/document/8746995/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 86145-86156
allfields_unstemmed	10.1109/ACCESS.2019.2925429 doi (DE-627)DOAJ056532474 (DE-599)DOAJ0f278123a5854d559d493d60a3ac7f2f DE-627 ger DE-627 rakwb eng TK1-9971 Jianmin Li verfasserin aut A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The moldable parallel task (MPT) is a kind of parallel task that their sub-tasks hold the resources exclusively, which has been widely used in different areas. Our paper focuses on the scheduling of moldable tasks when every sub-task supports time-slice. The time-slice is a consecutive time that the sub-task holds the resources exclusively. After every time-slice, the sub-task can be canceled, suspended, or continued. We give the model of MPTs and propose a scheduling method for MPTs: MC (a heuristic scheduling method supporting time-slice model on the cloud). The simulation results show that, even under a forecast accuracy of system load under 90% and 95%, MC reduces average waiting time and average execution time; at the same time, MC has a lower value in the percentages of unfinished tasks. Moldable parallel task speedup parallelism scheduling method Electrical engineering. Electronics. Nuclear engineering Ying Zhong verfasserin aut Xin Zhang verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 86145-86156 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:86145-86156 https://doi.org/10.1109/ACCESS.2019.2925429 kostenfrei https://doaj.org/article/0f278123a5854d559d493d60a3ac7f2f kostenfrei https://ieeexplore.ieee.org/document/8746995/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 86145-86156
allfieldsGer	10.1109/ACCESS.2019.2925429 doi (DE-627)DOAJ056532474 (DE-599)DOAJ0f278123a5854d559d493d60a3ac7f2f DE-627 ger DE-627 rakwb eng TK1-9971 Jianmin Li verfasserin aut A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The moldable parallel task (MPT) is a kind of parallel task that their sub-tasks hold the resources exclusively, which has been widely used in different areas. Our paper focuses on the scheduling of moldable tasks when every sub-task supports time-slice. The time-slice is a consecutive time that the sub-task holds the resources exclusively. After every time-slice, the sub-task can be canceled, suspended, or continued. We give the model of MPTs and propose a scheduling method for MPTs: MC (a heuristic scheduling method supporting time-slice model on the cloud). The simulation results show that, even under a forecast accuracy of system load under 90% and 95%, MC reduces average waiting time and average execution time; at the same time, MC has a lower value in the percentages of unfinished tasks. Moldable parallel task speedup parallelism scheduling method Electrical engineering. Electronics. Nuclear engineering Ying Zhong verfasserin aut Xin Zhang verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 86145-86156 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:86145-86156 https://doi.org/10.1109/ACCESS.2019.2925429 kostenfrei https://doaj.org/article/0f278123a5854d559d493d60a3ac7f2f kostenfrei https://ieeexplore.ieee.org/document/8746995/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 86145-86156
allfieldsSound	10.1109/ACCESS.2019.2925429 doi (DE-627)DOAJ056532474 (DE-599)DOAJ0f278123a5854d559d493d60a3ac7f2f DE-627 ger DE-627 rakwb eng TK1-9971 Jianmin Li verfasserin aut A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud 2019 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier The moldable parallel task (MPT) is a kind of parallel task that their sub-tasks hold the resources exclusively, which has been widely used in different areas. Our paper focuses on the scheduling of moldable tasks when every sub-task supports time-slice. The time-slice is a consecutive time that the sub-task holds the resources exclusively. After every time-slice, the sub-task can be canceled, suspended, or continued. We give the model of MPTs and propose a scheduling method for MPTs: MC (a heuristic scheduling method supporting time-slice model on the cloud). The simulation results show that, even under a forecast accuracy of system load under 90% and 95%, MC reduces average waiting time and average execution time; at the same time, MC has a lower value in the percentages of unfinished tasks. Moldable parallel task speedup parallelism scheduling method Electrical engineering. Electronics. Nuclear engineering Ying Zhong verfasserin aut Xin Zhang verfasserin aut In IEEE Access IEEE, 2014 7(2019), Seite 86145-86156 (DE-627)728440385 (DE-600)2687964-5 21693536 nnns volume:7 year:2019 pages:86145-86156 https://doi.org/10.1109/ACCESS.2019.2925429 kostenfrei https://doaj.org/article/0f278123a5854d559d493d60a3ac7f2f kostenfrei https://ieeexplore.ieee.org/document/8746995/ kostenfrei https://doaj.org/toc/2169-3536 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 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_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_213 GBV_ILN_230 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_2014 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 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_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 7 2019 86145-86156
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source	In IEEE Access 7(2019), Seite 86145-86156 volume:7 year:2019 pages:86145-86156
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topic_facet	Moldable parallel task speedup parallelism scheduling method Electrical engineering. Electronics. Nuclear engineering
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authorswithroles_txt_mv	Jianmin Li @@aut@@ Ying Zhong @@aut@@ Xin Zhang @@aut@@
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callnumber-first	T - Technology
author	Jianmin Li
spellingShingle	Jianmin Li misc TK1-9971 misc Moldable parallel task misc speedup misc parallelism misc scheduling method misc Electrical engineering. Electronics. Nuclear engineering A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud
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topic_title	TK1-9971 A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud Moldable parallel task speedup parallelism scheduling method
topic	misc TK1-9971 misc Moldable parallel task misc speedup misc parallelism misc scheduling method misc Electrical engineering. Electronics. Nuclear engineering
topic_unstemmed	misc TK1-9971 misc Moldable parallel task misc speedup misc parallelism misc scheduling method misc Electrical engineering. Electronics. Nuclear engineering
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title	A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud
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title_sort	scheduling method of moldable parallel tasks considering speedup and system load on the cloud
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title_auth	A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud
abstract	The moldable parallel task (MPT) is a kind of parallel task that their sub-tasks hold the resources exclusively, which has been widely used in different areas. Our paper focuses on the scheduling of moldable tasks when every sub-task supports time-slice. The time-slice is a consecutive time that the sub-task holds the resources exclusively. After every time-slice, the sub-task can be canceled, suspended, or continued. We give the model of MPTs and propose a scheduling method for MPTs: MC (a heuristic scheduling method supporting time-slice model on the cloud). The simulation results show that, even under a forecast accuracy of system load under 90% and 95%, MC reduces average waiting time and average execution time; at the same time, MC has a lower value in the percentages of unfinished tasks.
abstractGer	The moldable parallel task (MPT) is a kind of parallel task that their sub-tasks hold the resources exclusively, which has been widely used in different areas. Our paper focuses on the scheduling of moldable tasks when every sub-task supports time-slice. The time-slice is a consecutive time that the sub-task holds the resources exclusively. After every time-slice, the sub-task can be canceled, suspended, or continued. We give the model of MPTs and propose a scheduling method for MPTs: MC (a heuristic scheduling method supporting time-slice model on the cloud). The simulation results show that, even under a forecast accuracy of system load under 90% and 95%, MC reduces average waiting time and average execution time; at the same time, MC has a lower value in the percentages of unfinished tasks.
abstract_unstemmed	The moldable parallel task (MPT) is a kind of parallel task that their sub-tasks hold the resources exclusively, which has been widely used in different areas. Our paper focuses on the scheduling of moldable tasks when every sub-task supports time-slice. The time-slice is a consecutive time that the sub-task holds the resources exclusively. After every time-slice, the sub-task can be canceled, suspended, or continued. We give the model of MPTs and propose a scheduling method for MPTs: MC (a heuristic scheduling method supporting time-slice model on the cloud). The simulation results show that, even under a forecast accuracy of system load under 90% and 95%, MC reduces average waiting time and average execution time; at the same time, MC has a lower value in the percentages of unfinished tasks.
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title_short	A Scheduling Method of Moldable Parallel Tasks Considering Speedup and System Load on the Cloud
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