Authors:
Cássio L. M. Belusso
1
;
Sandro Sawicki
2
;
Vitor Basto-Fernandes
3
;
Rafael Z. Frantz
2
and
Fabricia Roos-Frantz
2
Affiliations:
1
Federal University of Fronteira Sul, Brazil
;
2
UNIJUÍ University, Brazil
;
3
University Institute of Lisbon, Portugal
Keyword(s):
Cloud Computing, Enterprise Application Integration, Price Modeling, Linear Regression, IaaS.
Related
Ontology
Subjects/Areas/Topics:
Coupling and Integrating Heterogeneous Data Sources
;
Databases and Information Systems Integration
;
Enterprise Information Systems
Abstract:
One of the main advances in information technology today is cloud computing. It is a great alternative for users to reduce costs related to the need to acquire and maintain computational infrastructure to develop, implement and execute software applications. Cloud computing services are offered by providers and can be classified into three main modalities: Platform-as-a-Service (PaaS), Software-as-a-Service (SaaS) and Infrastructure-as-a-Service (IaaS). In IaaS, the user has a virtual machine at their disposal with the desired computational resources at a given cost. Generally, the providers offer infrastructure services divided into instances, with pre-established configurations. The main challenge faced by companies is to choose the instance that best fits their needs among the many options offered by providers. Frequently, these companies need a large computational infrastructure to manage and improve their business processes and, due to the high cost of maintaining local infrastr
ucture, they have begun to migrate applications to the cloud in order to reduce these costs. In this paper, we introduce a proposal for price modeling of instances of virtual machines using linear regression. This approach analyzes a set of simplified hypotheses considering the following providers: Amazon EC2, Google Compute Engine and Microsoft Windows Azure.
(More)