Avaliação do Tempo de Retorno de Carbono na Migração de Contêineres entre Data Centers Distribuídos
Resumo
A migração de contêineres entre data centers permite acompanhar a eletricidade de menor carbono, mas o checkpoint, a compressão e a transferência consomem energia. Este trabalho estima o Tempo de Retorno de Carbono da migração a frio combinando a energia do CRIU e da compressão, medida com Intel RAPL numa carga HPC (NPB BT), a modelos de rede WAN entre 10 data centers. As operações locais respondem por 1% a 2% da pegada, e comprimir a imagem de alta entropia com xz gera uma dívida de carbono cinco a seis vezes maior que a do envio sem compressão. Sem compressão, o retorno ocorre entre 0,03 e 5,21 minutos, bem abaixo dos vales solares de 9 a 10 horas observados na Espanha e no norte da Califórnia em um dia de amostra, o que sugere a viabilidade dessa migração.Referências
Aksanli, B., Venkatesh, J., Monga, I., and Rosing, T. S. (2016). Renewable energy prediction for improved utilization and efficiency in datacenters and backbone networks. In Computational Sustainability, Studies in Computational Intelligence, pages 47–74. Springer, Cham.
Alhumaima, R. S., Jawad, S. R., and Al-Raweshidy, H. S. (2018). On the energy efficiency of virtual machines’ live migration in future cloud mobile broadband networks. In Haidine, A. and Aqqal, A., editors, Broadband Communications Networks: Recent Advances and Lessons from Practice, chapter 21. IntechOpen, London.
Aslan, J., Mayers, K., Koomey, J. G., and France, C. (2018). Electricity intensity of internet data transmission: Untangling the estimates. Journal of Industrial Ecology, 22(4):785–798.
Bailey, D. H., Barszcz, E., Barton, J. T., Browning, D. S., Carter, R. L., Dagum, L., Fatoohi, R. A., Frederickson, P. O., Lasinski, T. A., Schreiber, R. S., Simon, H. D., Venkatakrishnan, V., and Weeratunga, S. K. (1991). The NAS parallel benchmarks. In Proceedings of the 1991 ACM/IEEE Conference on Supercomputing, pages 158–165, New York, NY, USA. Association for Computing Machinery.
Baliga, J., Ayre, R., Hinton, K., Sorin, W. V., and Tucker, R. S. (2009). Energy consumption in optical IP networks. Journal of Lightwave Technology, 27(13):2391–2403.
Coroama, V. (2021). Investigating the inconsistencies among energy and energy intensity estimates of the internet metrics and harmonising values. Technical report, Swiss Federal Office of Energy SFOE.
CRIU (2026). CRIU: Checkpoint/Restore In Userspace. [link]. Acesso em: 10 out. 2026.
David, H., Gorbatov, E., Hanebutte, U. R., Khanna, R., and Le, C. (2010). RAPL: memory power estimation and capping. In Proceedings of the 16th ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED ’10), pages 189–194, New York, NY, USA. Association for Computing Machinery.
Electricity Maps (2026). CO2 emissions of electricity consumption. [link]. Acesso em: 10 out. 2026.
Guennebaud, G. and Bugeau, A. (2024). Energy consumption of data transfer: Intensity indicators versus absolute estimates. Journal of Industrial Ecology, 28(4):996–1008.
Kaur, K., Guillemin, F., and Sailhan, F. (2022). Container placement and migration strategies for cloud, fog, and edge data centers: A survey. International Journal of Network Management, 32(6):e2212.
Mytton, D., Lundén, D., and Malmodin, J. (2024). Network energy use not directly proportional to data volume: The power model approach for more reliable network energy consumption calculations. Journal of Industrial Ecology, 28(4):966–980.
Open Container Initiative (2026). runc. [link]. Acesso em: 10 out. 2026.
Pickartz, S., Eiling, N., Lankes, S., Razik, L., and Monti, A. (2016). Migrating LinuX Containers using CRIU. In Taufer, M., Mohr, B., and Kunkel, J. M., editors, ISC High Performance 2016 International Workshops, volume 9945 of Lecture Notes in Computer Science, pages 674–684, Cham. Springer International Publishing.
Qureshi, A., Weber, R., Balakrishnan, H., Guttag, J., and Maggs, B. (2009). Cutting the electric bill for internet-scale systems. In Proceedings of the ACM SIGCOMM 2009 Conference on Data Communication, pages 123–134, New York. ACM.
Rybina, K., Dargie, W., Strunk, A., and Schill, A. (2013). Investigation into the energy cost of live migration of virtual machines. In 2013 Sustainable Internet and ICT for Sustainability (SustainIT), pages 1–8, Palermo. IEEE.
Thiede, J., Bashir, N., Irwin, D., and Shenoy, P. (2023). Carbon Containers: A system-level facility for managing application-level carbon emissions. In Proceedings of the 2023 ACM Symposium on Cloud Computing (SoCC ’23), pages 17–31, New York, NY, USA. Association for Computing Machinery.
Tucker, R. S. (2011). Green optical communications—Part I: Energy limitations in transport. IEEE Journal of Selected Topics in Quantum Electronics, 17(2):245–260.
Vasconcelos, M. F. S., Cordeiro, D., and Dufossé, F. (2022). Indirect network impact on the energy consumption in multi-clouds for follow-the-renewables approaches. In Proceedings of the 11th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS), pages 44–55, Setúbal. SciTePress.
Alhumaima, R. S., Jawad, S. R., and Al-Raweshidy, H. S. (2018). On the energy efficiency of virtual machines’ live migration in future cloud mobile broadband networks. In Haidine, A. and Aqqal, A., editors, Broadband Communications Networks: Recent Advances and Lessons from Practice, chapter 21. IntechOpen, London.
Aslan, J., Mayers, K., Koomey, J. G., and France, C. (2018). Electricity intensity of internet data transmission: Untangling the estimates. Journal of Industrial Ecology, 22(4):785–798.
Bailey, D. H., Barszcz, E., Barton, J. T., Browning, D. S., Carter, R. L., Dagum, L., Fatoohi, R. A., Frederickson, P. O., Lasinski, T. A., Schreiber, R. S., Simon, H. D., Venkatakrishnan, V., and Weeratunga, S. K. (1991). The NAS parallel benchmarks. In Proceedings of the 1991 ACM/IEEE Conference on Supercomputing, pages 158–165, New York, NY, USA. Association for Computing Machinery.
Baliga, J., Ayre, R., Hinton, K., Sorin, W. V., and Tucker, R. S. (2009). Energy consumption in optical IP networks. Journal of Lightwave Technology, 27(13):2391–2403.
Coroama, V. (2021). Investigating the inconsistencies among energy and energy intensity estimates of the internet metrics and harmonising values. Technical report, Swiss Federal Office of Energy SFOE.
CRIU (2026). CRIU: Checkpoint/Restore In Userspace. [link]. Acesso em: 10 out. 2026.
David, H., Gorbatov, E., Hanebutte, U. R., Khanna, R., and Le, C. (2010). RAPL: memory power estimation and capping. In Proceedings of the 16th ACM/IEEE International Symposium on Low Power Electronics and Design (ISLPED ’10), pages 189–194, New York, NY, USA. Association for Computing Machinery.
Electricity Maps (2026). CO2 emissions of electricity consumption. [link]. Acesso em: 10 out. 2026.
Guennebaud, G. and Bugeau, A. (2024). Energy consumption of data transfer: Intensity indicators versus absolute estimates. Journal of Industrial Ecology, 28(4):996–1008.
Kaur, K., Guillemin, F., and Sailhan, F. (2022). Container placement and migration strategies for cloud, fog, and edge data centers: A survey. International Journal of Network Management, 32(6):e2212.
Mytton, D., Lundén, D., and Malmodin, J. (2024). Network energy use not directly proportional to data volume: The power model approach for more reliable network energy consumption calculations. Journal of Industrial Ecology, 28(4):966–980.
Open Container Initiative (2026). runc. [link]. Acesso em: 10 out. 2026.
Pickartz, S., Eiling, N., Lankes, S., Razik, L., and Monti, A. (2016). Migrating LinuX Containers using CRIU. In Taufer, M., Mohr, B., and Kunkel, J. M., editors, ISC High Performance 2016 International Workshops, volume 9945 of Lecture Notes in Computer Science, pages 674–684, Cham. Springer International Publishing.
Qureshi, A., Weber, R., Balakrishnan, H., Guttag, J., and Maggs, B. (2009). Cutting the electric bill for internet-scale systems. In Proceedings of the ACM SIGCOMM 2009 Conference on Data Communication, pages 123–134, New York. ACM.
Rybina, K., Dargie, W., Strunk, A., and Schill, A. (2013). Investigation into the energy cost of live migration of virtual machines. In 2013 Sustainable Internet and ICT for Sustainability (SustainIT), pages 1–8, Palermo. IEEE.
Thiede, J., Bashir, N., Irwin, D., and Shenoy, P. (2023). Carbon Containers: A system-level facility for managing application-level carbon emissions. In Proceedings of the 2023 ACM Symposium on Cloud Computing (SoCC ’23), pages 17–31, New York, NY, USA. Association for Computing Machinery.
Tucker, R. S. (2011). Green optical communications—Part I: Energy limitations in transport. IEEE Journal of Selected Topics in Quantum Electronics, 17(2):245–260.
Vasconcelos, M. F. S., Cordeiro, D., and Dufossé, F. (2022). Indirect network impact on the energy consumption in multi-clouds for follow-the-renewables approaches. In Proceedings of the 11th International Conference on Smart Cities and Green ICT Systems (SMARTGREENS), pages 44–55, Setúbal. SciTePress.
Publicado
03/11/2026
Como Citar
NASCIMENTO, Matheus V. R.; CORDEIRO, Daniel.
Avaliação do Tempo de Retorno de Carbono na Migração de Contêineres entre Data Centers Distribuídos. In: SIMPÓSIO EM SISTEMAS COMPUTACIONAIS DE ALTO DESEMPENHO (SSCAD), 27. , 2026, Natal/RN.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
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p. 595-608.
DOI: https://doi.org/10.5753/sscad.2026.34988.
