Modeling, run-time optimization and execution of distributed workflow applications in the JEE-based BeesyCluster environment
Abstract The paper presents a complete solution for modeling scientific and business workflow applications, static and just-in-time QoS selection of services and workflow execution in a real environment. The workflow application is modeled as an acyclic directed graph where nodes denote tasks and ed...
Ausführliche Beschreibung
Autor*in: |
Czarnul, Pawel [verfasserIn] |
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Format: |
Artikel |
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Sprache: |
Englisch |
Erschienen: |
2010 |
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Schlagwörter: |
Just-in-time service selection |
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Anmerkung: |
© The Author(s) 2010 |
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Übergeordnetes Werk: |
Enthalten in: The journal of supercomputing - Springer US, 1987, 63(2010), 1 vom: 13. Nov., Seite 46-71 |
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Übergeordnetes Werk: |
volume:63 ; year:2010 ; number:1 ; day:13 ; month:11 ; pages:46-71 |
Links: |
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DOI / URN: |
10.1007/s11227-010-0499-7 |
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Katalog-ID: |
OLC2033940659 |
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10.1007/s11227-010-0499-7 doi (DE-627)OLC2033940659 (DE-He213)s11227-010-0499-7-p DE-627 ger DE-627 rakwb eng 004 620 VZ Czarnul, Pawel verfasserin aut Modeling, run-time optimization and execution of distributed workflow applications in the JEE-based BeesyCluster environment 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2010 Abstract The paper presents a complete solution for modeling scientific and business workflow applications, static and just-in-time QoS selection of services and workflow execution in a real environment. The workflow application is modeled as an acyclic directed graph where nodes denote tasks and edges denote dependencies between the tasks. The BeesyCluster middleware is used to allow providers to publish services from sequential or parallel applications, from their servers or clusters. Optimization algorithms are proposed to select a capable service for each task so that a global criterion is optimized such as a product of workflow execution time and cost, a linear combination of those or minimization of the time with a cost constraint. The paper presents implementation details of the multithreaded workflow execution engine implemented in JEE. Several tests were performed for three different optimization goals for two business and scientific workflow applications. Finally, the overhead of the solution is presented. Workflow execution Just-in-time service selection Workflow management environment Workflow applications Scientific and business workflows Enthalten in The journal of supercomputing Springer US, 1987 63(2010), 1 vom: 13. Nov., Seite 46-71 (DE-627)13046466X (DE-600)740510-8 (DE-576)018667775 0920-8542 nnns volume:63 year:2010 number:1 day:13 month:11 pages:46-71 https://doi.org/10.1007/s11227-010-0499-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 AR 63 2010 1 13 11 46-71 |
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10.1007/s11227-010-0499-7 doi (DE-627)OLC2033940659 (DE-He213)s11227-010-0499-7-p DE-627 ger DE-627 rakwb eng 004 620 VZ Czarnul, Pawel verfasserin aut Modeling, run-time optimization and execution of distributed workflow applications in the JEE-based BeesyCluster environment 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2010 Abstract The paper presents a complete solution for modeling scientific and business workflow applications, static and just-in-time QoS selection of services and workflow execution in a real environment. The workflow application is modeled as an acyclic directed graph where nodes denote tasks and edges denote dependencies between the tasks. The BeesyCluster middleware is used to allow providers to publish services from sequential or parallel applications, from their servers or clusters. Optimization algorithms are proposed to select a capable service for each task so that a global criterion is optimized such as a product of workflow execution time and cost, a linear combination of those or minimization of the time with a cost constraint. The paper presents implementation details of the multithreaded workflow execution engine implemented in JEE. Several tests were performed for three different optimization goals for two business and scientific workflow applications. Finally, the overhead of the solution is presented. Workflow execution Just-in-time service selection Workflow management environment Workflow applications Scientific and business workflows Enthalten in The journal of supercomputing Springer US, 1987 63(2010), 1 vom: 13. Nov., Seite 46-71 (DE-627)13046466X (DE-600)740510-8 (DE-576)018667775 0920-8542 nnns volume:63 year:2010 number:1 day:13 month:11 pages:46-71 https://doi.org/10.1007/s11227-010-0499-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 AR 63 2010 1 13 11 46-71 |
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10.1007/s11227-010-0499-7 doi (DE-627)OLC2033940659 (DE-He213)s11227-010-0499-7-p DE-627 ger DE-627 rakwb eng 004 620 VZ Czarnul, Pawel verfasserin aut Modeling, run-time optimization and execution of distributed workflow applications in the JEE-based BeesyCluster environment 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2010 Abstract The paper presents a complete solution for modeling scientific and business workflow applications, static and just-in-time QoS selection of services and workflow execution in a real environment. The workflow application is modeled as an acyclic directed graph where nodes denote tasks and edges denote dependencies between the tasks. The BeesyCluster middleware is used to allow providers to publish services from sequential or parallel applications, from their servers or clusters. Optimization algorithms are proposed to select a capable service for each task so that a global criterion is optimized such as a product of workflow execution time and cost, a linear combination of those or minimization of the time with a cost constraint. The paper presents implementation details of the multithreaded workflow execution engine implemented in JEE. Several tests were performed for three different optimization goals for two business and scientific workflow applications. Finally, the overhead of the solution is presented. Workflow execution Just-in-time service selection Workflow management environment Workflow applications Scientific and business workflows Enthalten in The journal of supercomputing Springer US, 1987 63(2010), 1 vom: 13. Nov., Seite 46-71 (DE-627)13046466X (DE-600)740510-8 (DE-576)018667775 0920-8542 nnns volume:63 year:2010 number:1 day:13 month:11 pages:46-71 https://doi.org/10.1007/s11227-010-0499-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 AR 63 2010 1 13 11 46-71 |
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10.1007/s11227-010-0499-7 doi (DE-627)OLC2033940659 (DE-He213)s11227-010-0499-7-p DE-627 ger DE-627 rakwb eng 004 620 VZ Czarnul, Pawel verfasserin aut Modeling, run-time optimization and execution of distributed workflow applications in the JEE-based BeesyCluster environment 2010 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier © The Author(s) 2010 Abstract The paper presents a complete solution for modeling scientific and business workflow applications, static and just-in-time QoS selection of services and workflow execution in a real environment. The workflow application is modeled as an acyclic directed graph where nodes denote tasks and edges denote dependencies between the tasks. The BeesyCluster middleware is used to allow providers to publish services from sequential or parallel applications, from their servers or clusters. Optimization algorithms are proposed to select a capable service for each task so that a global criterion is optimized such as a product of workflow execution time and cost, a linear combination of those or minimization of the time with a cost constraint. The paper presents implementation details of the multithreaded workflow execution engine implemented in JEE. Several tests were performed for three different optimization goals for two business and scientific workflow applications. Finally, the overhead of the solution is presented. Workflow execution Just-in-time service selection Workflow management environment Workflow applications Scientific and business workflows Enthalten in The journal of supercomputing Springer US, 1987 63(2010), 1 vom: 13. Nov., Seite 46-71 (DE-627)13046466X (DE-600)740510-8 (DE-576)018667775 0920-8542 nnns volume:63 year:2010 number:1 day:13 month:11 pages:46-71 https://doi.org/10.1007/s11227-010-0499-7 lizenzpflichtig Volltext GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 AR 63 2010 1 13 11 46-71 |
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Abstract The paper presents a complete solution for modeling scientific and business workflow applications, static and just-in-time QoS selection of services and workflow execution in a real environment. The workflow application is modeled as an acyclic directed graph where nodes denote tasks and edges denote dependencies between the tasks. The BeesyCluster middleware is used to allow providers to publish services from sequential or parallel applications, from their servers or clusters. Optimization algorithms are proposed to select a capable service for each task so that a global criterion is optimized such as a product of workflow execution time and cost, a linear combination of those or minimization of the time with a cost constraint. The paper presents implementation details of the multithreaded workflow execution engine implemented in JEE. Several tests were performed for three different optimization goals for two business and scientific workflow applications. Finally, the overhead of the solution is presented. © The Author(s) 2010 |
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Abstract The paper presents a complete solution for modeling scientific and business workflow applications, static and just-in-time QoS selection of services and workflow execution in a real environment. The workflow application is modeled as an acyclic directed graph where nodes denote tasks and edges denote dependencies between the tasks. The BeesyCluster middleware is used to allow providers to publish services from sequential or parallel applications, from their servers or clusters. Optimization algorithms are proposed to select a capable service for each task so that a global criterion is optimized such as a product of workflow execution time and cost, a linear combination of those or minimization of the time with a cost constraint. The paper presents implementation details of the multithreaded workflow execution engine implemented in JEE. Several tests were performed for three different optimization goals for two business and scientific workflow applications. Finally, the overhead of the solution is presented. © The Author(s) 2010 |
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Abstract The paper presents a complete solution for modeling scientific and business workflow applications, static and just-in-time QoS selection of services and workflow execution in a real environment. The workflow application is modeled as an acyclic directed graph where nodes denote tasks and edges denote dependencies between the tasks. The BeesyCluster middleware is used to allow providers to publish services from sequential or parallel applications, from their servers or clusters. Optimization algorithms are proposed to select a capable service for each task so that a global criterion is optimized such as a product of workflow execution time and cost, a linear combination of those or minimization of the time with a cost constraint. The paper presents implementation details of the multithreaded workflow execution engine implemented in JEE. Several tests were performed for three different optimization goals for two business and scientific workflow applications. Finally, the overhead of the solution is presented. © The Author(s) 2010 |
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<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a22002652 4500</leader><controlfield tag="001">OLC2033940659</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20230504053739.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">200819s2010 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1007/s11227-010-0499-7</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC2033940659</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-He213)s11227-010-0499-7-p</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">004</subfield><subfield code="a">620</subfield><subfield code="q">VZ</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Czarnul, Pawel</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Modeling, run-time optimization and execution of distributed workflow applications in the JEE-based BeesyCluster environment</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2010</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="500" ind1=" " ind2=" "><subfield code="a">© The Author(s) 2010</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Abstract The paper presents a complete solution for modeling scientific and business workflow applications, static and just-in-time QoS selection of services and workflow execution in a real environment. 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