Uma Comparação de Múltiplas Políticas de Migração de Contêineres Suportadas pela Ferramenta CRIU
Resumo
A migração de contêineres entre servidores vem sendo utilizada para lidar com questões de desempenho e disponibilidade. Ferramentas como o Checkpoint Restoration In Userspace (CRIU) são utilizadas na migração de contêineres. Contudo, a seleção de uma política de migração adequada pode ser desafiadora. Nesse contexto, os modelos formais como rede de Petri estocástica (SPN) surgem como representações matemáticas para sistemas reais de migração de contêineres computacionais. Este artigo propõe dois modelos de redes de Petri estocásticas (SPN) com e sem estado absorvente. São avaliadas as métricas Migration Total Time (MTT), Mean Migration Time (MMT), probabilidade de descarte e utilização. O modelo com estado absorvente também permite calcular a função de distribuição de probabilidade acumulada (CDF).Referências
Bause, F. and Kritzinger, P. S. (2002). Stochastic petri nets, volume 1. Vieweg Wiesbaden.
Benjaponpitak, T., Karakate, M., and Sripanidkulchai, K. (2020). Enabling live migration of containerized applications across clouds. In IEEE INFOCOM 2020-IEEE Conference on Computer Communications, pages 2529–2538. IEEE.
Bolch, G., Greiner, S., De Meer, H., and Trivedi, K. S. (2006). Queueing networks and Markov chains: modeling and performance evaluation with computer science applications. John Wiley & Sons.
Chou, C. C., Chen, Y., Milojicic, D., Reddy, N., and Gratz, P. (2019). Optimizing post-copy live migration with system-level checkpoint using fabric-attached memory. In 2019 IEEE/ACM Workshop on Memory Centric High Performance Computing (MCHPC), pages 16–24. IEEE.
Dayo, A. O. (2021). A multi-containerized application using docker containers and kubernetes clusters. Int J Comput Appl, 183(44):55–60.
Di, Z., Shao, E., and Tan, G. (2021). High-performance migration tool for live container in a workflow. International Journal of Parallel Programming, 49:658–670.
Fan, W., Han, Z., Li, P., Zhou, J., Fan, J., and Wang, R. (2019). A live migration algorithm for containers based on resource locality. Journal of Signal Processing Systems, 91:1077–1089.
Govindaraj, K. and Artemenko, A. (2018). Container live migration for latency critical industrial applications on edge computing. In 2018 IEEE 23rd international conference on emerging technologies and factory automation (ETFA), volume 1, pages 83–90. IEEE.
Jain, R. (1990). The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling. John Wiley & Sons.
Jain, R. (1991). The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling, volume 1. Wiley New York.
Joy, A. M. (2015). Performance comparison between linux containers and virtual machines. In 2015 international conference on advances in computer engineering and applications, pages 342–346. IEEE.
Karhula, P., Janak, J., and Schulzrinne, H. (2019). Checkpointing and migration of iot edge functions. In Proceedings of the 2nd International Workshop on Edge Systems, Analytics and Networking, pages 60–65.
Kaur, A., Kumar, S., Gupta, D., Hamid, Y., Hamdi, M., Ksibi, A., Elmannai, H., and Saini, S. (2023). Algorithmic approach to virtual machine migration in cloud computing with updated sesa algorithm. Sensors, 23(13):6117.
Machen, A., Wang, S., Leung, K. K., Ko, B. J., and Salonidis, T. (2017). Live service migration in mobile edge clouds. IEEE Wireless Communications, 25(1):140–147.
Maciel, P., Matos, R., Silva, B., Figueiredo, J., Oliveira, D., Fé, I., Maciel, R., and Dantas, J. (2017). Mercury: Performance and dependability evaluation of systems with exponential, expolynomial, and general distributions. In 2017 IEEE 22nd Pacific Rim international symposium on dependable computing (PRDC), pages 50–57. IEEE.
Maciel, P. R., Lins, R. D., and Cunha, P. R. (1996). Introdução às redes de Petri e aplicações. UNICAMP-Instituto de Computacao Sao Paulo, Brazil.
Maheshwari, S., Choudhury, S., Seskar, I., and Raychaudhuri, D. (2018). Traffic-aware dynamic container migration for real-time support in mobile edge clouds. In 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), pages 1–6. IEEE.
Marsan, M. A., Balbo, G., Conte, G., Donatelli, S., and Franceschinis, G. (1998). Modelling with generalized stochastic petri nets. ACM SIGMETRICS performance evaluation review, 26(2):2.
Nelson, R. (2013). Probability, stochastic processes, and queueing theory: the mathematics of computer performance modeling. Springer Science & Business Media.
Pecholt, J., Huber, M., and Wessel, S. (2021). Live migration of operating system containers in encrypted virtual machines. In Proceedings of the 2021 on Cloud Computing Security Workshop, pages 125–137.
Pinheiro, T., Silva, F. A., Fe, I., Kosta, S., and Maciel, P. (2018). Performance and data traffic analysis of mobile cloud environments. In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 4100–4105. IEEE.
Puliafito, C., Vallati, C., Mingozzi, E., Merlino, G., Longo, F., and Puliafito, A. (2019). Container migration in the fog: A performance evaluation. Sensors, 19(7):1488.
Ramanathan, S., Kondepu, K., Razo, M., Tacca, M., Valcarenghi, L., and Fumagalli, A. (2021). Live migration of virtual machine and container based mobile core network components: A comprehensive study. IEEE Access, 9:105082–105100.
Silvaa, B., Maciela, P. R. M., Zimmermannb, A., and Brilhantea, J. (2014). Survivability evaluation of disaster tolerant cloud computing systems. In Proc. Probabilistic Safety Assessment & Management conference, page 12.
Torre, R., Urbano, E., Salah, H., Nguyen, G. T., and Fitzek, F. H. (2019). Towards a better understanding of live migration performance with docker containers. In European Wireless 2019; 25th European Wireless Conference, pages 1–6. VDE.
Benjaponpitak, T., Karakate, M., and Sripanidkulchai, K. (2020). Enabling live migration of containerized applications across clouds. In IEEE INFOCOM 2020-IEEE Conference on Computer Communications, pages 2529–2538. IEEE.
Bolch, G., Greiner, S., De Meer, H., and Trivedi, K. S. (2006). Queueing networks and Markov chains: modeling and performance evaluation with computer science applications. John Wiley & Sons.
Chou, C. C., Chen, Y., Milojicic, D., Reddy, N., and Gratz, P. (2019). Optimizing post-copy live migration with system-level checkpoint using fabric-attached memory. In 2019 IEEE/ACM Workshop on Memory Centric High Performance Computing (MCHPC), pages 16–24. IEEE.
Dayo, A. O. (2021). A multi-containerized application using docker containers and kubernetes clusters. Int J Comput Appl, 183(44):55–60.
Di, Z., Shao, E., and Tan, G. (2021). High-performance migration tool for live container in a workflow. International Journal of Parallel Programming, 49:658–670.
Fan, W., Han, Z., Li, P., Zhou, J., Fan, J., and Wang, R. (2019). A live migration algorithm for containers based on resource locality. Journal of Signal Processing Systems, 91:1077–1089.
Govindaraj, K. and Artemenko, A. (2018). Container live migration for latency critical industrial applications on edge computing. In 2018 IEEE 23rd international conference on emerging technologies and factory automation (ETFA), volume 1, pages 83–90. IEEE.
Jain, R. (1990). The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling. John Wiley & Sons.
Jain, R. (1991). The art of computer systems performance analysis: techniques for experimental design, measurement, simulation, and modeling, volume 1. Wiley New York.
Joy, A. M. (2015). Performance comparison between linux containers and virtual machines. In 2015 international conference on advances in computer engineering and applications, pages 342–346. IEEE.
Karhula, P., Janak, J., and Schulzrinne, H. (2019). Checkpointing and migration of iot edge functions. In Proceedings of the 2nd International Workshop on Edge Systems, Analytics and Networking, pages 60–65.
Kaur, A., Kumar, S., Gupta, D., Hamid, Y., Hamdi, M., Ksibi, A., Elmannai, H., and Saini, S. (2023). Algorithmic approach to virtual machine migration in cloud computing with updated sesa algorithm. Sensors, 23(13):6117.
Machen, A., Wang, S., Leung, K. K., Ko, B. J., and Salonidis, T. (2017). Live service migration in mobile edge clouds. IEEE Wireless Communications, 25(1):140–147.
Maciel, P., Matos, R., Silva, B., Figueiredo, J., Oliveira, D., Fé, I., Maciel, R., and Dantas, J. (2017). Mercury: Performance and dependability evaluation of systems with exponential, expolynomial, and general distributions. In 2017 IEEE 22nd Pacific Rim international symposium on dependable computing (PRDC), pages 50–57. IEEE.
Maciel, P. R., Lins, R. D., and Cunha, P. R. (1996). Introdução às redes de Petri e aplicações. UNICAMP-Instituto de Computacao Sao Paulo, Brazil.
Maheshwari, S., Choudhury, S., Seskar, I., and Raychaudhuri, D. (2018). Traffic-aware dynamic container migration for real-time support in mobile edge clouds. In 2018 IEEE International Conference on Advanced Networks and Telecommunications Systems (ANTS), pages 1–6. IEEE.
Marsan, M. A., Balbo, G., Conte, G., Donatelli, S., and Franceschinis, G. (1998). Modelling with generalized stochastic petri nets. ACM SIGMETRICS performance evaluation review, 26(2):2.
Nelson, R. (2013). Probability, stochastic processes, and queueing theory: the mathematics of computer performance modeling. Springer Science & Business Media.
Pecholt, J., Huber, M., and Wessel, S. (2021). Live migration of operating system containers in encrypted virtual machines. In Proceedings of the 2021 on Cloud Computing Security Workshop, pages 125–137.
Pinheiro, T., Silva, F. A., Fe, I., Kosta, S., and Maciel, P. (2018). Performance and data traffic analysis of mobile cloud environments. In 2018 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pages 4100–4105. IEEE.
Puliafito, C., Vallati, C., Mingozzi, E., Merlino, G., Longo, F., and Puliafito, A. (2019). Container migration in the fog: A performance evaluation. Sensors, 19(7):1488.
Ramanathan, S., Kondepu, K., Razo, M., Tacca, M., Valcarenghi, L., and Fumagalli, A. (2021). Live migration of virtual machine and container based mobile core network components: A comprehensive study. IEEE Access, 9:105082–105100.
Silvaa, B., Maciela, P. R. M., Zimmermannb, A., and Brilhantea, J. (2014). Survivability evaluation of disaster tolerant cloud computing systems. In Proc. Probabilistic Safety Assessment & Management conference, page 12.
Torre, R., Urbano, E., Salah, H., Nguyen, G. T., and Fitzek, F. H. (2019). Towards a better understanding of live migration performance with docker containers. In European Wireless 2019; 25th European Wireless Conference, pages 1–6. VDE.
Publicado
20/05/2024
Como Citar
FEITOSA, Leonel; BARBOSA, Vandirleya; SABINO, Arthur; LIMA, Luiz Nelson; FÉ, Iure; SILVA, Bruno; SILVA, Francisco Airton.
Uma Comparação de Múltiplas Políticas de Migração de Contêineres Suportadas pela Ferramenta CRIU. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 42. , 2024, Niterói/RJ.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2024
.
p. 742-755.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2024.1467.
