Resources allocation and scheduling approaches for business process applications in Cloud contexts
Identifieur interne : 004169 ( Hal/Curation ); précédent : 004168; suivant : 004170Resources allocation and scheduling approaches for business process applications in Cloud contexts
Auteurs : Kahina Bessai [France] ; Samir Youcef [France] ; Ammar Oulamara [France] ; Claude Godart [France] ; Selmin Nurcan [France]Source :
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Abstract
In the last years, the Cloud computing environment has emerged as new execution support of business process. However, despite the proven benefits of using Cloud to run business process, users lack guidance for choosing between multiple offerings while taking into account several objectives, which are often conflicting. On the other side, elastic computing, such as Amazon EC2, allows users to allocate and release compute resources (virtual machines) on-demand and pay only for what they use. Therefore, it is reasonable to assume that the number of virtual machines is infinite. This feature of Clouds has been called "illusion of infinite resources''. Moreover, including human resources in the business process execution process make the automated execution of workflow difficult, due to the fact that the number of human resources is finite. In this paper, we develop an allocation strategy for Cloud computing platform taking into account the above characteristics. More precisely, we propose three complementary bi-criterion approaches for resources allocation and scheduling of business process on distributed Cloud resources.
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75231 Paris Cedex 05</addrLine><country key="FR"></country></address><ref type="url">http://www.univ-paris1.fr/</ref></desc></org></tutelle></tutelles></hal:affiliation><country>France</country></affiliation></author></analytic></biblStruct></sourceDesc></fileDesc><profileDesc><textClass><keywords scheme="mix" xml:lang="en"><term>Cloud computing</term><term>bi-objective optimization</term><term>business process</term><term>scheduling</term></keywords></textClass></profileDesc></teiHeader><front><div type="abstract" xml:lang="en">In the last years, the Cloud computing environment has emerged as new execution support of business process. However, despite the proven benefits of using Cloud to run business process, users lack guidance for choosing between multiple offerings while taking into account several objectives, which are often conflicting. On the other side, elastic computing, such as Amazon EC2, allows users to allocate and release compute resources (virtual machines) on-demand and pay only for what they use. Therefore, it is reasonable to assume that the number of virtual machines is infinite. This feature of Clouds has been called "illusion of infinite resources''. Moreover, including human resources in the business process execution process make the automated execution of workflow difficult, due to the fact that the number of human resources is finite. In this paper, we develop an allocation strategy for Cloud computing platform taking into account the above characteristics. More precisely, we propose three complementary bi-criterion approaches for resources allocation and scheduling of business process on distributed Cloud resources.</div></front></TEI><hal api="V3"><titleStmt><title xml:lang="en">Resources allocation and scheduling approaches for business process applications in Cloud contexts</title><author role="aut"><persName><forename type="first">Kahina</forename><surname>Bessai</surname></persName><email></email><idno type="halauthor">683765</idno><affiliation ref="#struct-74131"></affiliation></author><author role="aut"><persName><forename type="first">Samir</forename><surname>Youcef</surname></persName><email>samir.youcef@loria.fr</email><idno type="halauthor">782301</idno><affiliation ref="#struct-107894"></affiliation></author><author role="aut"><persName><forename type="first">Ammar</forename><surname>Oulamara</surname></persName><email>oulamara@loria.fr</email><idno type="halauthor">54154</idno><affiliation ref="#struct-107894"></affiliation></author><author role="aut"><persName><forename type="first">Claude</forename><surname>Godart</surname></persName><email>Claude.Godart@loria.fr</email><idno type="halauthor">59021</idno><affiliation ref="#struct-107894"></affiliation></author><author role="aut"><persName><forename type="first">Selmin</forename><surname>Nurcan</surname></persName><email>selmin.nurcan@univ-paris1.fr</email><idno type="halauthor">437596</idno><affiliation ref="#struct-74131"></affiliation></author><editor role="depositor"><persName><forename>Samir</forename><surname>Youcef</surname></persName><email>samir.youcef@loria.fr</email></editor></titleStmt><editionStmt><edition n="v1" type="current"><date type="whenSubmitted">2012-11-12 23:02:31</date><date type="whenWritten">2012-02-01</date><date type="whenModified">2015-09-21 11:13:17</date><date type="whenReleased">2012-11-13 10:42:21</date><date type="whenProduced">2012-12-03</date><date type="whenEndEmbargoed">2012-11-12</date><ref type="file" target="https://hal.inria.fr/hal-00751209/document"><date notBefore="2012-11-12"></date></ref><ref type="file" subtype="author" n="1" target="https://hal.inria.fr/hal-00751209/file/main.pdf"><date notBefore="2012-11-12"></date></ref></edition><respStmt><resp>contributor</resp><name key="177157"><persName><forename>Samir</forename><surname>Youcef</surname></persName><email>samir.youcef@loria.fr</email></name></respStmt></editionStmt><publicationStmt><distributor>CCSD</distributor><idno type="halId">hal-00751209</idno><idno type="halUri">https://hal.inria.fr/hal-00751209</idno><idno type="halBibtex">bessai:hal-00751209</idno><idno type="halRefHtml">CloudCom 2012 - 4th IEEE International Conference on Cloud Computing Technology and Science, Dec 2012, Taipei, Taiwan. 2012</idno><idno type="halRef">CloudCom 2012 - 4th IEEE International Conference on Cloud Computing Technology and Science, Dec 2012, Taipei, Taiwan. 2012</idno></publicationStmt><seriesStmt><idno type="stamp" n="UNIV-PARIS1">Université Panthéon-Sorbonne - Paris I</idno><idno type="stamp" n="CRI">Centre de Recherche en Informatique de Paris 1</idno><idno type="stamp" n="CNRS">CNRS - Centre national de la recherche scientifique</idno><idno type="stamp" n="INRIA">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="INRIA-LORRAINE">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA2">Publications du LORIA</idno><idno type="stamp" n="INRIA-NANCY-GRAND-EST">INRIA Nancy - Grand Est</idno><idno type="stamp" n="LORIA-NSS" p="LORIA">Réseaux, systèmes et services</idno><idno type="stamp" n="LORIA">LORIA - Laboratoire Lorrain de Recherche en Informatique et ses Applications</idno><idno type="stamp" n="INRIA_TEST">INRIA - Institut National de Recherche en Informatique et en Automatique</idno><idno type="stamp" n="UNIV-LORRAINE">Université de Lorraine</idno></seriesStmt><notesStmt><note type="audience" n="2">International</note><note type="invited" n="0">No</note><note type="popular" n="0">No</note><note type="peer" n="1">Yes</note><note type="proceedings" n="1">Yes</note></notesStmt><sourceDesc><biblStruct><analytic><title xml:lang="en">Resources allocation and scheduling approaches for business process applications in Cloud contexts</title><author role="aut"><persName><forename type="first">Kahina</forename><surname>Bessai</surname></persName><idno type="halAuthorId">683765</idno><affiliation ref="#struct-74131"></affiliation></author><author role="aut"><persName><forename type="first">Samir</forename><surname>Youcef</surname></persName><email>samir.youcef@loria.fr</email><idno type="halAuthorId">782301</idno><affiliation ref="#struct-107894"></affiliation></author><author role="aut"><persName><forename type="first">Ammar</forename><surname>Oulamara</surname></persName><email>oulamara@loria.fr</email><idno type="halAuthorId">54154</idno><affiliation ref="#struct-107894"></affiliation></author><author role="aut"><persName><forename type="first">Claude</forename><surname>Godart</surname></persName><email>Claude.Godart@loria.fr</email><idno type="halAuthorId">59021</idno><affiliation ref="#struct-107894"></affiliation></author><author role="aut"><persName><forename type="first">Selmin</forename><surname>Nurcan</surname></persName><email>selmin.nurcan@univ-paris1.fr</email><idno type="halAuthorId">437596</idno><affiliation ref="#struct-74131"></affiliation></author></analytic><monogr><meeting><title>CloudCom 2012 - 4th IEEE International Conference on Cloud Computing Technology and Science</title><date type="start">2012-12-03</date><date type="end">2012-12-06</date><settlement>Taipei</settlement><country key="TW">Taiwan</country></meeting><imprint><date type="datePub">2012-12-03</date></imprint></monogr></biblStruct></sourceDesc><profileDesc><langUsage><language ident="en">English</language></langUsage><textClass><keywords scheme="author"><term xml:lang="en">Cloud computing</term><term xml:lang="en">business process</term><term xml:lang="en">scheduling</term><term xml:lang="en">bi-objective optimization</term></keywords><classCode scheme="halDomain" n="info.info-wb">Computer Science [cs]/Web</classCode><classCode scheme="halTypology" n="COMM">Conference papers</classCode></textClass><abstract xml:lang="en">In the last years, the Cloud computing environment has emerged as new execution support of business process. However, despite the proven benefits of using Cloud to run business process, users lack guidance for choosing between multiple offerings while taking into account several objectives, which are often conflicting. On the other side, elastic computing, such as Amazon EC2, allows users to allocate and release compute resources (virtual machines) on-demand and pay only for what they use. Therefore, it is reasonable to assume that the number of virtual machines is infinite. This feature of Clouds has been called "illusion of infinite resources''. Moreover, including human resources in the business process execution process make the automated execution of workflow difficult, due to the fact that the number of human resources is finite. In this paper, we develop an allocation strategy for Cloud computing platform taking into account the above characteristics. More precisely, we propose three complementary bi-criterion approaches for resources allocation and scheduling of business process on distributed Cloud resources.</abstract></profileDesc></hal></record>Pour manipuler ce document sous Unix (Dilib)
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