A power reduction approach to green cloud computing

Authors

DOI:

https://doi.org/10.33448/rsd-v12i7.42407

Keywords:

Green cloud computing; Cloud simulation; Energy efficiency.

Abstract

As cloud computing becomes increasingly prevalent in our daily lives and the business environment, it is essential that we are aware and proactive in managing the environmental impact of this technology. Green cloud computing is an approach that seeks to reduce energy consumption and CO2 emissions associated with cloud computing, while still providing the necessary functionality and performance. Through the use of simulators, such as CloudSim Plus, and the implementation of efficient algorithms for resource management, this study demonstrated that it is possible to achieve significant improvements in energy efficiency, reductions in operational costs, and a decrease in environmental impact without reducing computational capacity. An improvement of at least 49% in energy efficiency was observed, a reduction of at least 7% in direct costs, and a decrease of 50% in equivalent CO2 emissions. It is important to emphasize that these improvements were achieved without compromising the performance of the systems, as the processing times remained unchanged.

Author Biographies

Thiago Nelson Faria dos Reis, Universidade Federal do Maranhão

I am Bachelor's degree in Computer Science from the Federal University of Maranhão. He completed his Master's degree in Computer Science and is currently a PhD candidate in Computer Science at the Federal University of Maranhão, specializing in Green Cloud Computing. He also has a specialization in Systems Analysis and Design from UFMA, as well as a specialization in Computer Networks from ESAB. Additionally, he holds an MBA in Project Management from Faculdade Pitágoras and is a Project Manager with certifications in Project Management Professional (PMP) from the Project Management Institute (PMI), Scrum Master PSM-II, PSM-I, and SPS from Scrum.org. He currently works as a Judicial Analyst at the State Court of Maranhão, is a University Professor, and works as a Consultant in Information Technology at Faculdade Santa Terezinha. He has professional experience in Computer Science, with a focus on Database, Software Engineering, Security, Forensic Science, Project Management, Business Intelligence (BI), Cloud Computing, and Artificial Intelligence.

Mário Meireles Teixeira, Universidade Federal do Maranhão

Graduated in Computer Science from the Federal University of Maranhão (1992) and master's degree (1997) and doctorate (2004) in Computer Science and Computational Mathematics from the University of São Paulo (ICMC-USP). He did postdoctoral studies at Boston University (2014-2015), specializing in cloud computing. He is currently an Associate Professor at the Federal University of Maranhão and professor of the master's and doctorate in Computer Science (PPGCC and DCCMAPI), as well as Information Technology Coordinator at UNA-SUS / UFMA. He has experience in the field of Computer Science, working mainly on the following topics: distributed systems, performance evaluation, web services, cloud computing and educational games.

Carlos de Salles Soares Neto, Universidade Federal do Maranhão

Graduation at Ciência da Computação from Universidade Federal do Maranhão (2000), master at Computer Science from Pontifícia Universidade Católica do Rio de Janeiro (2003) and doctorate at Doutorado de Informática from Pontifícia Universidade Católica do Rio de Janeiro (2010). Has experience in Computer Science, acting on the following subjects: tv digital, nested context language, ginga-ncl, aplicações multimídia and ncl.

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Published

08/07/2023

How to Cite

REIS, T. N. F. dos .; TEIXEIRA, M. M. .; SOARES NETO, C. de S. A power reduction approach to green cloud computing. Research, Society and Development, [S. l.], v. 12, n. 7, p. e1812742407, 2023. DOI: 10.33448/rsd-v12i7.42407. Disponível em: https://www.rsdjournal.org/index.php/rsd/article/view/42407. Acesso em: 15 may. 2024.

Issue

Vol. 12 No. 7

Section

Exact and Earth Sciences

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Copyright (c) 2023 Thiago Nelson Faria dos Reis; Mário Meireles Teixeira; Carlos de Salles Soares Neto

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