Profiling SLAs for cloud system infrastructures and user interactions

M Emilia Cambronero; Adrián Bernal; Valentín Valero; Pablo C Cañizares; Alberto Núñez

doi:10.7717/peerj-cs.513

Profiling SLAs for cloud system infrastructures and user interactions

PeerJ Comput Sci. 2021 May 12:7:e513. doi: 10.7717/peerj-cs.513. eCollection 2021.

Authors

M Emilia Cambronero¹, Adrián Bernal¹, Valentín Valero¹, Pablo C Cañizares², Alberto Núñez³

Affiliations

¹ Albacete Research Institute of Informatics, Department of Computer Science, University of Castilla La Mancha, Albacete, Spain.
² School of Informatics, Autonomous University of Madrid, Madrid, Spain.
³ School of Informatics, Complutense University of Madrid, Madrid, Spain.

Abstract

Cloud computing has emerged as a cutting-edge technology which is widely used by both private and public institutions, since it eliminates the capital expense of buying, maintaining, and setting up both hardware and software. Clients pay for the services they use, under the so-called Service Level Agreements (SLAs), which are the contracts that establish the terms and costs of the services. In this paper, we propose the CloudCost UML profile, which allows the modeling of cloud architectures and the users' behavior when they interact with the cloud to request resources. We then investigate how to increase the profits of cloud infrastructures by using price schemes. For this purpose, we distinguish between two types of users in the SLAs: regular and high-priority users. Regular users do not require a continuous service, so they can wait to be attended to. In contrast, high-priority users require a constant and immediate service, so they pay a greater price for their services. In addition, a computer-aided design tool, called MSCC (Modeling SLAs Cost Cloud), has been implemented to support the CloudCost profile, which enables the creation of specific cloud scenarios, as well as their edition and validation. Finally, we present a complete case study to illustrate the applicability of the CloudCost profile, thus making it possible to draw conclusions about how to increase the profits of the cloud infrastructures studied by adjusting the different cloud parameters and the resource configuration.

Keywords: Cloud; Design and simulation tools; Model development; Profit improvement; SLAs.

Grants and funding

This work was supported by the Spanish Ministry of Science and Innovation (co-financed by European Union FEDER funds) project “FAME (Formal modeling and advanced testing methods. Applications to medicine and computing systems) and MASSIVE (Engineering adaptive software by and for the people in a highly connected world)”, references RTI2018-093608-B-C32 and RTI2018-095255-B-I00. There was also support from the Junta de Comunidades de Castilla-La Mancha project SBPLY/17/180501/000276/01 (cofunded with FEDER funds, EU), the Region of Madrid (grant number FORTE-CM, S2018/TCS-4314), and the Madrid Government (Comunidad de Madrid-Spain) under the Multiannual Agreement with the Complutense University as part of the Program to Stimulate Research for Young Doctors in the context of the V PRICIT (Regional Programme of Research and Technological Innovation) under grant PR65/19-22452. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.