Task scheduling characterisation in enterprise application integration

dc.contributor.authorFreire, D. L.
dc.contributor.authorFrantz, R. Z.
dc.contributor.authorRoos-Frantz, F.
dc.contributor.authorBasto-Fernandes, V.
dc.date.accessioned2022-06-24T16:10:05Z
dc.date.available2022-06-24T16:10:05Z
dc.date.issued2022
dc.date.updated2022-06-24T17:09:11Z
dc.description.abstractCloud computing allows enterprises to incorporate applications and computational resources as services, and thus, enterprises can concentrate on their business processes, without concerning the development, configuration and maintenance of these applications and resources. Integration platforms are one of these services that allow enterprises to integrate applications in order to reduce the maintenance costs and operations of the integration of on-premises platforms. However, high performance on resources offered by the cloud, demands improvement in task scheduling of integration platforms. Our literature review has identified a lack of studies in the field of enterprise application integration, focusing on specificities and vulnerabilities of the task scheduling of integration processes. This is a pioneer work regarding the characterisation of the scheduling of tasks of integration processes. We propose a ranking according to their conceptual models and apply this ranking to five integration processes. Then, we have statistically analysed the influence of each component of their conceptual models on the performance of the execution of these integration processes. We characterise the task scheduling of integration processes and presented a mathematical equation for the makespan as a function of the components of this characterisation. This study can guide software engineers in the optimal task scheduling for integration processes, which can improve the performance runtime systems regarding using the computational resources and result in minimisation of costs of companies.eng
dc.description.versioninfo:eu-repo/semantics/acceptedVersion
dc.identifier.doi10.1007/s11227-021-04119-2
dc.identifier.issn0920-8542
dc.identifier.urihttp://hdl.handle.net/10071/25706
dc.journalThe Journal of Supercomputing
dc.language.isoeng
dc.number5
dc.pagination6528 - 6566
dc.peerreviewedyes
dc.publisherSpringer
dc.relation309315/2020-4
dc.relation17/2551-0001206-2
dc.rightsopen access
dc.subjectDynamic task schedulingeng
dc.subjectIntegration applicationeng
dc.subjectIntegration platformeng
dc.subjectStep-wise multiple linear regressioneng
dc.subjectWorkflow schedulingeng
dc.subject.fosDomínio/Área Científica::Ciências Naturais::Ciências da Computação e da Informaçãopor
dc.subject.fosDomínio/Área Científica::Engenharia e Tecnologia::Engenharia Eletrotécnica, Eletrónica e Informáticapor
dc.titleTask scheduling characterisation in enterprise application integrationeng
dc.typearticle
dc.volume78
degois.publication.firstPage6528
degois.publication.issue5
degois.publication.lastPage6566
degois.publication.titleTask scheduling characterisation in enterprise application integrationeng
dspace.entity.typePublicationen
iscte.alternateIdentifiers.scopus2-s2.0-85117735258
iscte.alternateIdentifiers.wosWOS:000710062400004
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-83758
iscte.subject.odsIndústria, inovação e infraestruturaspor

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