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Reseach Article

A Cloud Service Broker for Cost Effective Infrastructure Selection using Multiple Deployment Options

by Raphael Gomes, Geovany Rodrigues, Gilberto Lobo
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 175 - Number 32
Year of Publication: 2020
Authors: Raphael Gomes, Geovany Rodrigues, Gilberto Lobo

Raphael Gomes, Geovany Rodrigues, Gilberto Lobo . A Cloud Service Broker for Cost Effective Infrastructure Selection using Multiple Deployment Options. International Journal of Computer Applications. 175, 32 ( Nov 2020), 1-8. DOI=10.5120/ijca2020920874

@article{ 10.5120/ijca2020920874,
author = { Raphael Gomes, Geovany Rodrigues, Gilberto Lobo },
title = { A Cloud Service Broker for Cost Effective Infrastructure Selection using Multiple Deployment Options },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2020 },
volume = { 175 },
number = { 32 },
month = { Nov },
year = { 2020 },
issn = { 0975-8887 },
pages = { 1-8 },
numpages = {9},
url = { },
doi = { 10.5120/ijca2020920874 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-07T00:40:03.067291+05:30
%A Raphael Gomes
%A Geovany Rodrigues
%A Gilberto Lobo
%T A Cloud Service Broker for Cost Effective Infrastructure Selection using Multiple Deployment Options
%J International Journal of Computer Applications
%@ 0975-8887
%V 175
%N 32
%P 1-8
%D 2020
%I Foundation of Computer Science (FCS), NY, USA

The multiplicity of cloud service providers and the wide variety of resources types and regions makes selecting services a challenging task, which becomes even more complex when considering different cloud deployment models to meet the applications’ specifics that will use these resources. For this, among the criteria used in selecting cloud resources, the cost is rated one of the most essential. Given this, this paper presents a cloud service broker’s design and implementation for resource selection, taking into account different options, including the variation of cloud service providers, regions, and cloud deployment models. The proposed tool is based on other contributions that are also described in this work: 1) the design and construction of an ontology with concepts on the representation of computing resources, with associated reasoning processes; and 2) an on-premises infrastructure cost estimation strategy using a Total Cost of Ownership analysis. A qualitative evaluation considering productivity and accuracy is also presented, demonstrating the advantages of the proposed tool over other existing options.

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Index Terms

Computer Science
Information Sciences


Cloud service selection cost optimization deployment models ontology TCO