Mobile Cloud computing architecture for massively parallelizable geometric computation

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dc.contributorArquitecturas Inteligentes Aplicadas (AIA)es_ES
dc.contributor.authorSánchez-Ribes, Víctor-
dc.contributor.authorMora, Higinio-
dc.contributor.authorSobecki, Andrzej-
dc.contributor.authorMora Gimeno, Francisco José-
dc.contributor.otherUniversidad de Alicante. Departamento de Tecnología Informática y Computaciónes_ES
dc.date.accessioned2020-11-06T11:46:01Z-
dc.date.available2020-11-06T11:46:01Z-
dc.date.issued2020-12-
dc.identifier.citationComputers in Industry. 2020, 123: 103336. https://doi.org/10.1016/j.compind.2020.103336es_ES
dc.identifier.issn0166-3615 (Print)-
dc.identifier.issn1872-6194 (Online)-
dc.identifier.urihttp://hdl.handle.net/10045/110154-
dc.description.abstractCloud Computing is one of the most disruptive technologies of this century. This technology has been widely adopted in many areas of the society. In the field of manufacturing industry, it can be used to provide advantages in the execution of the complex geometric computation algorithms involved on CAD/CAM processes. The idea proposed in this research consists in outsourcing part of the load to be computed in the client machines to the cloud through the Mobile Cloud Computing paradigm. This practice gives substantial benefits to both the clients and the software-provider in terms of costs, flexibility, ubiquity and performance. In this document, an outsourcing architecture is proposed based on this paradigm. Extensive experiments have been done using highly parallelizable computational geometry operations to show the strengths and weaknesses of the proposal in combination of specialized computing platforms in the cloud. The results suggest that there are some issues that affect the overall performance and the stability of the QoS: the network communication delay, and the number of simultaneous clients and multiple requests. Some solutions have been proposed to face these challenges.es_ES
dc.description.sponsorshipThis work was supported by the Spanish Research Agency (AEI) and the European Regional Development Fund (ERDF) under project CloudDriver4Industry TIN2017-89266-R, and by the Conselleria of Innovation, Universities, Science and Digital Society of the Community of Valencia, Spain, within the program of support for research under project AICO/2020/206.es_ES
dc.languageenges_ES
dc.publisherElsevieres_ES
dc.rights© 2020 Elsevier B.V.es_ES
dc.subjectGPU computinges_ES
dc.subjectGPUes_ES
dc.subjectCUDAes_ES
dc.subjectCloud offloadinges_ES
dc.subjectCloud computinges_ES
dc.subject.otherArquitectura y Tecnología de Computadoreses_ES
dc.titleMobile Cloud computing architecture for massively parallelizable geometric computationes_ES
dc.typeinfo:eu-repo/semantics/articlees_ES
dc.peerreviewedsies_ES
dc.identifier.doi10.1016/j.compind.2020.103336-
dc.relation.publisherversionhttps://doi.org/10.1016/j.compind.2020.103336es_ES
dc.rights.accessRightsinfo:eu-repo/semantics/restrictedAccesses_ES
dc.relation.projectIDinfo:eu-repo/grantAgreement/AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2013-2016/TIN2017-89266-R-
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