A heuristic approach to the multicriteria design of IaaS cloud infrastructures for Big Data applications

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dc.contributor.authorArostegi, María
dc.contributor.authorTorre-Bastida, Ana
dc.contributor.authorBilbao, Miren Nekane
dc.contributor.authorDel Ser, Javier
dc.contributor.institutionIA
dc.contributor.institutionTecnalia Research & Innovation
dc.contributor.institutionHPA
dc.date.accessioned2024-07-24T12:14:58Z
dc.date.available2024-07-24T12:14:58Z
dc.date.issued2018-10
dc.descriptionPublisher Copyright: © 2018 John Wiley & Sons, Ltd.
dc.description.abstractThe rapid growth of new computing paradigms such as Cloud Computing and Big Data has unleashed great opportunities for companies to shift their business model towards a fully digital strategy. A major obstacle in this matter is the requirement of highly specialized ICT infrastructures that are expensive and difficult to manage. It is at this point that the IaaS (infrastructure as a service) model offers an efficient and cost-affordable solution to supply companies with their required computing resources. In the Big Data context, it is often a hard task to design an optimal IaaS solution that meets user requirements. In this context, we propose a methodology to optimize the definition of IaaS cloud models for hosting Big Data platforms, following a threefold criterion: cost, reliability, and computing capacity. Specifically, the proposed methodology hinges on evolutionary heuristics in order to find IaaS configurations in the cloud that optimally balance such objectives. We also define measures to quantify the aforementioned metrics over a Big Data platform hosted within an IaaS cloud model. The proposed method is validated by using real information from three IaaS providers and three Big Data platforms. The obtained results provide an insightful input for system managers when initially designing cloud infrastructures for Big Data applications.en
dc.description.sponsorshipThis work has been funded in part by the Basque Government under the ELKARTEK program (BID3ABI project).
dc.description.statusPeer reviewed
dc.identifier.citationArostegi , M , Torre-Bastida , A , Bilbao , M N & Del Ser , J 2018 , ' A heuristic approach to the multicriteria design of IaaS cloud infrastructures for Big Data applications ' , Expert Systems , vol. 35 , no. 5 , e12259 . https://doi.org/10.1111/exsy.12259
dc.identifier.doi10.1111/exsy.12259
dc.identifier.issn0266-4720
dc.identifier.urihttps://hdl.handle.net/11556/4526
dc.identifier.urlhttp://www.scopus.com/inward/record.url?scp=85040536325&partnerID=8YFLogxK
dc.language.isoeng
dc.relation.ispartofExpert Systems
dc.relation.projectIDEusko Jaurlaritza
dc.rightsinfo:eu-repo/semantics/restrictedAccess
dc.subject.keywordsBig Data
dc.subject.keywordsCloud Computing
dc.subject.keywordsIaaS
dc.subject.keywordsmultiobjective heuristics
dc.subject.keywordsNSGA-II
dc.subject.keywordsControl and Systems Engineering
dc.subject.keywordsTheoretical Computer Science
dc.subject.keywordsComputational Theory and Mathematics
dc.subject.keywordsArtificial Intelligence
dc.subject.keywordsSDG 9 - Industry, Innovation, and Infrastructure
dc.titleA heuristic approach to the multicriteria design of IaaS cloud infrastructures for Big Data applicationsen
dc.typejournal article
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