Proposta Sustentável Para Data Center: Revisão Sistemática de Literatura
Resumo
A crescente demanda por dados leva a um aumento no consumo de energia em data centers. A sustentabilidade em data centers é uma resposta essencial às demandas da sociedade contemporânea, pois oferece oportunidades de economia de energia, benefícios para as empresas e uso de tecnologias. No entanto, existem desafios na medição precisa do consumo de energia.
Referências
Basmadjian, R. (2019). Flexibility-based energy and demand management in data centers: a case study for cloud computing. Energies, 12(17):3301.
Dumitrescu, C., Plesca, A., Adam, M., Nituca, C., and Dragomir, A. (2018). Methods for reducing energy consumption, optimization in operational data centers. In 2018 International Conference and Exposition on Electrical And Power Engineering (EPE), pages 0483–0486. IEEE.
Heikkinen, D. (2023). The need for green data centers in modern society: Technology, economy and environmental sustainability. mpra.
Jnr, B. A., Majid, M. A., and Romli, A. (2018). A descriptive study towards green computing practice application for data centers in it based industries. In MATEC web of conferences, volume 150, page 05048. EDP Sciences.
Kotowski, J., Oko, J., et al. (2018). Green computing and energy storage systems. In E3S Web of Conferences, volume 44. EDP Sciences.
Kumar, N. (2023). Energy efficient framework formulation based on green computing for devops automation. Computer Science e Application.
Lykou, G., Mentzelioti, D., and Gritzalis, D. (2018). A new methodology toward effectively assessing data center sustainability. Computers e Security, 76:327–340.
Masanet, E. and Lei, N. (2020). How much energy do data centers really use. Aspen Global Change Institute.
Patterson, D., Gonzalez, J., Hölzle, U., Le, Q., Liang, C., Munguia, L.-M., Rothchild, D., So, D. R., Texier, M., and Dean, J. (2022). The carbon footprint of machine learning training will plateau, then shrink. Computer, 55(7):18–28.
Prasanna, T. and Singh, K. P. (2023). Improving energy efficiency in cloud data centers through an brownout software system strategy based on containers. https://eurchembull.com.
Dumitrescu, C., Plesca, A., Adam, M., Nituca, C., and Dragomir, A. (2018). Methods for reducing energy consumption, optimization in operational data centers. In 2018 International Conference and Exposition on Electrical And Power Engineering (EPE), pages 0483–0486. IEEE.
Heikkinen, D. (2023). The need for green data centers in modern society: Technology, economy and environmental sustainability. mpra.
Jnr, B. A., Majid, M. A., and Romli, A. (2018). A descriptive study towards green computing practice application for data centers in it based industries. In MATEC web of conferences, volume 150, page 05048. EDP Sciences.
Kotowski, J., Oko, J., et al. (2018). Green computing and energy storage systems. In E3S Web of Conferences, volume 44. EDP Sciences.
Kumar, N. (2023). Energy efficient framework formulation based on green computing for devops automation. Computer Science e Application.
Lykou, G., Mentzelioti, D., and Gritzalis, D. (2018). A new methodology toward effectively assessing data center sustainability. Computers e Security, 76:327–340.
Masanet, E. and Lei, N. (2020). How much energy do data centers really use. Aspen Global Change Institute.
Patterson, D., Gonzalez, J., Hölzle, U., Le, Q., Liang, C., Munguia, L.-M., Rothchild, D., So, D. R., Texier, M., and Dean, J. (2022). The carbon footprint of machine learning training will plateau, then shrink. Computer, 55(7):18–28.
Prasanna, T. and Singh, K. P. (2023). Improving energy efficiency in cloud data centers through an brownout software system strategy based on containers. https://eurchembull.com.
Publicado
30/10/2023
Como Citar
GUIMARÃES, Josiany B.; AMARIS, Marcos.
Proposta Sustentável Para Data Center: Revisão Sistemática de Literatura. In: ESCOLA REGIONAL DE ALTO DESEMPENHO NORTE 2 (ERAD-NO2) E ESCOLA REGIONAL DE APRENDIZADO DE MÁQUINA E INTELIGÊNCIA ARTIFICIAL NORTE 2 (ERAMIA-NO2), 3. , 2023, Belém/PA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2023
.
p. 33-36.
DOI: https://doi.org/10.5753/erad-no2.2023.236293.
