Migração de máquinas virtuais como estratégia para data centers sustentáveis
Resumo
O crescente uso de data centers geodistribuídos impulsiona a capacidade da computação em nuvem, mas também eleva o consumo de energia e as emissões de gases do efeito estufa. Neste trabalho, investigamos, por meio de simulação, algoritmos de escalonamento aplicados a esses data centers, visando à redução do impacto ambiental. A abordagem proposta explora políticas de migração de máquinas virtuais (VMs) para indicar estratégias que aliem desempenho e sustentabilidade. A expectativa é que os experimentos subsidiem a implementação de soluções de escalonamento capazes de minimizar emissões de gases do efeito estufa e promover operações mais sustentáveis em infraestruturas de larga escala.Referências
Buyya, R., Vecchiola, C., and Selvi, S. T. (2013). Mastering Cloud Computing: Foundations and Applications Programming. Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 1st edition.
Clark, C., Fraser, K., Hand, S., Hansen, J. G., Jul, E., Limpach, C., Pratt, I., and Warfield, A. (2005). Live migration of virtual machines. In Proceedings of the 2nd Conference on Symposium on Networked Systems Design & Implementation - Volume 2, NSDI’05, pages 273—-286, USA. USENIX Association.
Kumar, M., Sharma, S., Goel, A., and Singh, S. (2019). A comprehensive survey for scheduling techniques in cloud computing. J. of Network and Computer App., 143.
Masanet, E., Shehabi, A., Lei, N., Smith, S., and Koomey, J. (2020). Recalibrating global data center energy-use estimates. Science, 367(6481):984–986.
Paul, P. K. and Ghose, M. K. (2018). Why green computing and green information sciences have potentialities in academics and ischools: Practice and educational perspectives. In SenGupta, S., Zobaa, A. F., Sherpa, K. S., and Bhoi, A. K., editors, Advances in Smart Grid and Renewable Energy, pages 103–112, Singapore. Springer Singapore.
Popek, G. J. and Goldberg, R. P. (1974). Formal requirements for virtualizable third generation architectures. Commun. ACM, 17(7):412–421.
Shehabi, A., Smith, S. J., Hubbard, A., Newkirk, A., Lei, N., Siddik, M. A. B., Holecek, B., Koomey, J., Masanet, E., and Sartor, D. (2024). 2024 united states data center energy usage report. Technical Report LBNL-2001637, Lawrence Berkeley National Laboratory, Berkeley, California.
Silva Filho, M. C., Oliveira, R. L., Monteiro, C. C., Inácio, P. R. M., and Freire, M. M. (2017). Cloudsim plus: A cloud computing simulation framework pursuing software engineering principles for improved modularity, extensibility and correctness. In 2017 IFIP/IEEE Symp. on Integrated Network and Service Management, pages 400–406.
Vasconcelos, M., Cordeiro, D., Da Costa, G., Dufossé, F., Nicod, J.-M., and Rehn-Sonigo, V. (2023). Optimal sizing of a globally distributed low carbon cloud federation. In 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid), pages 203–215. IEEE.
Clark, C., Fraser, K., Hand, S., Hansen, J. G., Jul, E., Limpach, C., Pratt, I., and Warfield, A. (2005). Live migration of virtual machines. In Proceedings of the 2nd Conference on Symposium on Networked Systems Design & Implementation - Volume 2, NSDI’05, pages 273—-286, USA. USENIX Association.
Kumar, M., Sharma, S., Goel, A., and Singh, S. (2019). A comprehensive survey for scheduling techniques in cloud computing. J. of Network and Computer App., 143.
Masanet, E., Shehabi, A., Lei, N., Smith, S., and Koomey, J. (2020). Recalibrating global data center energy-use estimates. Science, 367(6481):984–986.
Paul, P. K. and Ghose, M. K. (2018). Why green computing and green information sciences have potentialities in academics and ischools: Practice and educational perspectives. In SenGupta, S., Zobaa, A. F., Sherpa, K. S., and Bhoi, A. K., editors, Advances in Smart Grid and Renewable Energy, pages 103–112, Singapore. Springer Singapore.
Popek, G. J. and Goldberg, R. P. (1974). Formal requirements for virtualizable third generation architectures. Commun. ACM, 17(7):412–421.
Shehabi, A., Smith, S. J., Hubbard, A., Newkirk, A., Lei, N., Siddik, M. A. B., Holecek, B., Koomey, J., Masanet, E., and Sartor, D. (2024). 2024 united states data center energy usage report. Technical Report LBNL-2001637, Lawrence Berkeley National Laboratory, Berkeley, California.
Silva Filho, M. C., Oliveira, R. L., Monteiro, C. C., Inácio, P. R. M., and Freire, M. M. (2017). Cloudsim plus: A cloud computing simulation framework pursuing software engineering principles for improved modularity, extensibility and correctness. In 2017 IFIP/IEEE Symp. on Integrated Network and Service Management, pages 400–406.
Vasconcelos, M., Cordeiro, D., Da Costa, G., Dufossé, F., Nicod, J.-M., and Rehn-Sonigo, V. (2023). Optimal sizing of a globally distributed low carbon cloud federation. In 2023 IEEE/ACM 23rd International Symposium on Cluster, Cloud and Internet Computing (CCGrid), pages 203–215. IEEE.
Publicado
28/05/2025
Como Citar
SILVA, Guilherme Fernandes Moraes da; CORDEIRO, Daniel.
Migração de máquinas virtuais como estratégia para data centers sustentáveis. In: ESCOLA REGIONAL DE ALTO DESEMPENHO DE SÃO PAULO (ERAD-SP), 16. , 2025, São José do Rio Preto/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 70-73.
DOI: https://doi.org/10.5753/eradsp.2025.9715.
