Please use this identifier to cite or link to this item: http://hdl.handle.net/2381/38890
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dc.contributor.authorFerreira, C. H. G.-
dc.contributor.authorEstrella, J. C.-
dc.contributor.authorNunes, L. H.-
dc.contributor.authorReiff-Marganiec, Stephan-
dc.contributor.authorBatista, B. G.-
dc.contributor.authorNakamura, L. H. V.-
dc.contributor.authorLeite, D.-
dc.contributor.authorPeixoto, M.-
dc.contributor.authorLibardi, R. M. D. O.-
dc.date.accessioned2016-12-09T16:15:42Z-
dc.date.issued2017-05-25-
dc.identifier.citationIEEE International Conference on Communications 21-25 May 2017, Paris, France Bridging People, Communities, and Culturesen
dc.identifier.uriTBAen
dc.identifier.urihttp://hdl.handle.net/2381/38890-
dc.description.abstractThis paper presents a cloud approach for low cost capacity planning evaluations. To perform these evaluations we have to specify and measure the workload on the target system to discover issues and make the necessary adjustments. However, due to high costs, these evaluations are usually done using simulations, which does not consider stochastic effects. We propose to use a tool named PEESOS, a generic and flexible approach to apply real workloads and measure used resources on these real systems. As a proof of concept, our case study use a real ticket sales service to evaluate the influence of scalability in the resource provisioning to show how PEESOS can lower the cost of such real evaluations. The results show the efficiency and savings that we can obtain using PEESOS for large-scale capacity planning evaluations before the real services are deployed. This approach can avoid several problems that real services faces when they launch.en
dc.description.sponsorshipThe authors would like to thank National Council for Scientific and Technological Development (CNPQ, process 139917/2014- 4) and S˜ao Paulo Research Fundation (FAPESP, processes 11/09524-7, 13/26420-6, 11/12670-5), for the support of this research.en
dc.language.isoenen
dc.publisherInstitute of Electrical and Electronics Engineers (IEEE)en
dc.rightsCreative Commons “Attribution Non-Commercial No Derivatives” licence CC BY-NC-ND, further details of which can be found via the following link: http://creativecommons.org/licenses/by-nc-nd/4.0/ Archived with reference to SHERPA/RoMEO and publisher website.en
dc.subjectCapacity Planningen
dc.subjectWorkload Generationen
dc.subjectService-Oriented Systemsen
dc.titleA low cost workload generation approach through the cloud for capacity planning in Service-Oriented Systemsen
dc.typeConference Paperen
dc.identifier.doiTBA-
dc.description.statusPeer-revieweden
dc.description.versionPost-printen
dc.description.presentedIEEE International Conference on Communications 21-25 May 2017, Paris, France Bridging People, Communities, and Culturesen
dc.date.end2017-05-25-
dc.date.start2017-05-21-
pubs.organisational-group/Organisationen
pubs.organisational-group/Organisation/COLLEGE OF SCIENCE AND ENGINEERINGen
pubs.organisational-group/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Computer Scienceen
dc.rights.embargodate10000-01-01-
dc.dateaccepted2016-07-13-
Appears in Collections:Conference Papers & Presentations, Dept. of Computer Science

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