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Price forecasting for spot instances in Cloud computing

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Price forecasting for spot instances in Cloud computing

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dc.contributor.author Cai, Zhicheng es_ES
dc.contributor.author Li, Xiaoping es_ES
dc.contributor.author Ruiz García, Rubén es_ES
dc.contributor.author Li, Qianmu es_ES
dc.date.accessioned 2020-06-24T03:31:23Z
dc.date.available 2020-06-24T03:31:23Z
dc.date.issued 2018-02 es_ES
dc.identifier.issn 0167-739X es_ES
dc.identifier.uri http://hdl.handle.net/10251/146877
dc.description.abstract [EN] Big data applications usually need to rent a large number of virtual machines from Cloud computing providers. As a result of the policies employed by Cloud providers, the prices of spot virtual machine instances behavior stochastically. Spot prices (prices of spot instances) fluctuate greatly or have multiple regimes. Choosing virtual machines according to trends in prices is helpful in decreasing the resource rental cost. Existing price prediction methods are unable to accurately predict prices in these environments. As a result, a dynamic-ARIMA and two markov regime-switching autoregressive model based forecasting methods have been developed in this paper. Experimental results show that the proposals are better than the existing MonthAR in most scenarios. (C) 2017 Elsevier B.V. All rights reserved. es_ES
dc.description.sponsorship The authors would like to thank the reviewers for their constructive and useful comments. This work is supported by the National Natural Science Foundation of China (Grant No. 61602243 and No. 61572127), the Natural Science Foundation of Jiangsu Province (Grant No. BK20160846), Jiangsu Key Laboratory of Image and Video Understanding for Social Safety (Grant No. 30916014107). Ruben Ruiz is partially supported by the Spanish Ministry of Economy and Competitiveness, under the project "SCHEYARD" (No. DPI2015-65895-R) financed by FEDER funds. es_ES
dc.language Inglés es_ES
dc.publisher Elsevier es_ES
dc.relation.ispartof Future Generation Computer Systems es_ES
dc.rights Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) es_ES
dc.subject Cloud computing es_ES
dc.subject Spot price es_ES
dc.subject Forecast es_ES
dc.subject Markov regime-switching es_ES
dc.subject Scheduling es_ES
dc.subject.classification ESTADISTICA E INVESTIGACION OPERATIVA es_ES
dc.title Price forecasting for spot instances in Cloud computing es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1016/j.future.2017.09.038 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSFC//61572127/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/NSFC//61602243/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/Natural Science Foundation of Jiangsu Province//BK20160846/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/Jiangsu Key Laboratory of Image and Video Understanding for Social Safety//30916014107/ es_ES
dc.relation.projectID info:eu-repo/grantAgreement/MINECO//DPI2015-65895-R/ES/OPTIMIZATION OF SCHEDULING PROBLEMS IN CONTAINER YARDS/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Estadística e Investigación Operativa Aplicadas y Calidad - Departament d'Estadística i Investigació Operativa Aplicades i Qualitat es_ES
dc.description.bibliographicCitation Cai, Z.; Li, X.; Ruiz García, R.; Li, Q. (2018). Price forecasting for spot instances in Cloud computing. Future Generation Computer Systems. 79:38-53. https://doi.org/10.1016/j.future.2017.09.038 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.1016/j.future.2017.09.038 es_ES
dc.description.upvformatpinicio 38 es_ES
dc.description.upvformatpfin 53 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 79 es_ES
dc.relation.pasarela S\383625 es_ES
dc.contributor.funder National Science Foundation, China es_ES
dc.contributor.funder National Natural Science Foundation of China es_ES
dc.contributor.funder Natural Science Foundation of Jiangsu Province es_ES
dc.contributor.funder Jiangsu Key Laboratory of Image and Video Understanding for Social Safety, China es_ES
dc.contributor.funder Ministerio de Economía y Competitividad es_ES


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