A proposal of Infrastructure-as-a-Service providers pricing model using linear regression
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10071/17609 |
Resumo: | The increasing demand for companies to reduce the IT infrastructure (on-premise) are driving the adoption of a type of cloud computing category known as Infrastructure-as-a-Service (IaaS) to provide virtualized computing resources over the Internet. However, the choice of an instance of virtual machine whose configuration is able to meet the demands of the company is a complex task, especially concerning the price charged by providers. The lack of transparency of the mechanism of definition of the prices adopted by providers makes difficult the decision-making process, considering the influence of several factors on the final price of the instances, among them the geographical location of the data center. In view of this problem, this work presents a new proposal of price modeling of instances using multiple linear regression model, including the geographical location of the data center as one of variables of the model. To verify the accuracy of the regression model proposed, the calculated prices were compared to real prices charged by IaaS providers Amazon EC2, Google Cloud Platform e Microsoft Azure. |
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A proposal of Infrastructure-as-a-Service providers pricing model using linear regressionCloud ComputingEnterprise Application IntegrationInfrastructure-as-a-ServiceLinear RegressionPricing ModelThe increasing demand for companies to reduce the IT infrastructure (on-premise) are driving the adoption of a type of cloud computing category known as Infrastructure-as-a-Service (IaaS) to provide virtualized computing resources over the Internet. However, the choice of an instance of virtual machine whose configuration is able to meet the demands of the company is a complex task, especially concerning the price charged by providers. The lack of transparency of the mechanism of definition of the prices adopted by providers makes difficult the decision-making process, considering the influence of several factors on the final price of the instances, among them the geographical location of the data center. In view of this problem, this work presents a new proposal of price modeling of instances using multiple linear regression model, including the geographical location of the data center as one of variables of the model. To verify the accuracy of the regression model proposed, the calculated prices were compared to real prices charged by IaaS providers Amazon EC2, Google Cloud Platform e Microsoft Azure.Editora UPF2019-03-14T16:22:01Z2018-01-01T00:00:00Z20182019-03-14T16:21:48Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/17609eng2176-664910.5335/rbca.v10i2.7839Belusso, C. M. L.Sawicki, S.Basto-Fernandes, V.Frantz, R. Z.Roos-Frantz, F.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2023-11-09T17:50:31Zoai:repositorio.iscte-iul.pt:10071/17609Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-19T22:24:56.425870Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse |
dc.title.none.fl_str_mv |
A proposal of Infrastructure-as-a-Service providers pricing model using linear regression |
title |
A proposal of Infrastructure-as-a-Service providers pricing model using linear regression |
spellingShingle |
A proposal of Infrastructure-as-a-Service providers pricing model using linear regression Belusso, C. M. L. Cloud Computing Enterprise Application Integration Infrastructure-as-a-Service Linear Regression Pricing Model |
title_short |
A proposal of Infrastructure-as-a-Service providers pricing model using linear regression |
title_full |
A proposal of Infrastructure-as-a-Service providers pricing model using linear regression |
title_fullStr |
A proposal of Infrastructure-as-a-Service providers pricing model using linear regression |
title_full_unstemmed |
A proposal of Infrastructure-as-a-Service providers pricing model using linear regression |
title_sort |
A proposal of Infrastructure-as-a-Service providers pricing model using linear regression |
author |
Belusso, C. M. L. |
author_facet |
Belusso, C. M. L. Sawicki, S. Basto-Fernandes, V. Frantz, R. Z. Roos-Frantz, F. |
author_role |
author |
author2 |
Sawicki, S. Basto-Fernandes, V. Frantz, R. Z. Roos-Frantz, F. |
author2_role |
author author author author |
dc.contributor.author.fl_str_mv |
Belusso, C. M. L. Sawicki, S. Basto-Fernandes, V. Frantz, R. Z. Roos-Frantz, F. |
dc.subject.por.fl_str_mv |
Cloud Computing Enterprise Application Integration Infrastructure-as-a-Service Linear Regression Pricing Model |
topic |
Cloud Computing Enterprise Application Integration Infrastructure-as-a-Service Linear Regression Pricing Model |
description |
The increasing demand for companies to reduce the IT infrastructure (on-premise) are driving the adoption of a type of cloud computing category known as Infrastructure-as-a-Service (IaaS) to provide virtualized computing resources over the Internet. However, the choice of an instance of virtual machine whose configuration is able to meet the demands of the company is a complex task, especially concerning the price charged by providers. The lack of transparency of the mechanism of definition of the prices adopted by providers makes difficult the decision-making process, considering the influence of several factors on the final price of the instances, among them the geographical location of the data center. In view of this problem, this work presents a new proposal of price modeling of instances using multiple linear regression model, including the geographical location of the data center as one of variables of the model. To verify the accuracy of the regression model proposed, the calculated prices were compared to real prices charged by IaaS providers Amazon EC2, Google Cloud Platform e Microsoft Azure. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-01-01T00:00:00Z 2018 2019-03-14T16:22:01Z 2019-03-14T16:21:48Z |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://hdl.handle.net/10071/17609 |
url |
http://hdl.handle.net/10071/17609 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
2176-6649 10.5335/rbca.v10i2.7839 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
application/pdf |
dc.publisher.none.fl_str_mv |
Editora UPF |
publisher.none.fl_str_mv |
Editora UPF |
dc.source.none.fl_str_mv |
reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação instacron:RCAAP |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
reponame_str |
Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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1799134812039020544 |