Container Migration Performance Evaluation: An Approach Based on Stochastic Petri Nets
Resumo
Containerization has emerged as a transformative technology in modern data centers, enabling efficient resource management and improving operational flexibility across various applications. While often associated with platforms like Docker and Kubernetes, container-based solutions are widely integrated into cloud environments such as AWS, Microsoft Azure, and Google Cloud. In large-scale distributed systems, efficient container migration is crucial to manage server downtime, consolidate resources, and ensure reliability in mobile edge computing scenarios. The problem with evaluating container migration performance lies in the high cost and computational demand of real-world experiments. Assessing different migration strategies efficiently remains a challenge, particularly for stateful containers, which require structured modeling approaches to quantify their impact on system performance. The proposal of this study is to develop Stochastic Petri Net (SPN) models to assess container migration strategies. The approach includes two models—one incorporating an absorbing state and another without—analyzing key migration techniques: Cold, PreCopy, PostCopy, and Hybrid. These models evaluate critical performance metrics, including Migration Total Time (MTT), Mean Migration Time (MMT), utilization, discard probability, and migration rate. Furthermore, a sensitivity analysis based on the Design of Experiments (DoE) was conducted for the Hybrid migration strategy to identify key performance factors. The conclusion of this research is that by providing an analytical framework for container migration evaluation, it enhances the understanding of migration performance dynamics and supports decision-making in cloud and edge computing infrastructures.
Palavras-chave:
Container, Live Migration, Performance, Petri Net, Sensitivity Analysis
Referências
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Conforti, L., Virdis, A., Puliafito, C., and Mingozzi, E. (2021). Extending the quic protocol to support live container migration at the edge. In 2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), pages 61–70. IEEE.
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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.
Feitosa, L., Barbosa, V., Sabino, A., Lima, L. N., Fé, I., Silva, B., and Silva, F. A. (2024). Uma comparação de múltiplas políticas de migração de contêineres suportadas pela ferramenta criu. In Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC), pages 742–755. SBC.
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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.
Kotikalapudi, S. V. N. (2017). Comparing live migration between linux containers and kernel virtual machine: investigation study in terms of parameters.
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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.
Majeed, A. A., Kilpatrick, P., Spence, I., and Varghese, B. (2020). Modelling fog offloading performance. In 2020 IEEE 4th International Conference on Fog and Edge Computing (ICFEC), pages 29–38. IEEE.
Malhotra, M. and Trivedi, K. S. (1995). Dependability modeling using petri-nets. IEEE Transactions on Reliability, 44(3):428–440.
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.
Pickartz, S., Eiling, N., Lankes, S., Razik, L., and Monti, A. (2016). Migrating linux containers using criu. In High Performance Computing: ISC High Performance 2016 International Workshops, pages 674–684. Springer.
Ramanathan, S., Kondepu, K., Razo, M., Tacca, M., Valcarenghi, L., and Fumagalli, A. (2021a). Live migration of virtual machine and container based mobile core network components: A comprehensive study. IEEE Access, 9:105082–105100.
Ramanathan, S., Kondepu, K., Zhang, T., Mirkhanzadeh, B., Razo, M., Tacca, M., Valcarenghi, L., and Fumagalli, A. (2021b). A comprehensive study of virtual machine and container based core network components migration in openroadm sdn-enabled network. arXiv preprint arXiv:2108.12509.
Requeno, J.-I., Merseguer, J., and Bernardi, S. (2017). Performance analysis of apache storm applications using stochastic petri nets. In 2017 IEEE International Conference on Information Reuse and Integration (IRI), pages 411–418. IEEE.
Silva, F. A., Fé, I., and Gonçalves, G. (2021). Stochastic models for performance and cost analysis of a hybrid cloud and fog architecture. The Journal of Supercomputing, 77(2):1537–1561.
Smimite, O. and Afdel, K. (2019). Impact of hybrid virtualization using vm and container on live migration and cloud performance. In Lecture Notes in Real-Time Intelligent Systems, pages 196–208. Springer.
Statista (2023). Container technology - statistics and facts.
Stoyanov, R. and Kollingbaum, M. J. (2018). Efficient live migration of linux containers. In High Performance Computing: ISC High Performance 2018 International Workshops, pages 184–193. Springer.
Tay, Y., Gaurav, K., and Karkun, P. (2017). A performance comparison of containers and virtual machines in workload migration context. In 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW), pages 61–66. IEEE.
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.
Turnbull, J. (2014). The Docker Book: Containerization is the new virtualization. James Turnbull, San Francisco, CA.
Varasteh, A. and Goudarzi, M. (2015). Server consolidation techniques in virtualized data centers: A survey. IEEE Systems Journal, 11(2):772–783.
Vaughan-Nichols, S. (2022). Migrating from VMware to OpenStack: Optimizing your Infrastructure to Save Money and Avoid Vendor-Lock-in. Acessado em: 2 de novembro de 2024.
Xu, B., Wu, S., Xiao, J., Jin, H., Zhang, Y., Shi, G., Lin, T., Rao, J., Yi, L., and Jiang, J. (2020). Sledge: Towards efficient live migration of docker containers. In 2020 IEEE 13th International Conference on Cloud Computing (CLOUD), pages 321–328. IEEE.
Al-Dhuraibi, Y., Paraiso, F., Djarallah, N., and Merle, P. (2017). Autonomic vertical elasticity of docker containers with elasticdocker. In 2017 IEEE 10th International Conference on Cloud Computing (CLOUD), pages 472–479. IEEE.
Authors, T. K. (2021). Kubernetes Documentation. Acessado em: 2 de novembro de 2024.
Baccarelli, E., Scarpiniti, M., and Momenzadeh, A. (2018). Fog-supported delay-constrained energy-saving live migration of vms over multipath tcp/ip 5g connections. IEEE Access, 6:42327–42354.
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.
Bhardwaj, A. and Rama Krishna, C. (2022). A container-based technique to improve virtual machine migration in cloud computing. IETE Journal of Research, 68(1):401–416.
Carvalho, D., Rodrigues, L., Endo, P. T., Kosta, S., and Silva, F. A. (2020). Mobile edge computing performance evaluation using stochastic petri nets. In 2020 IEEE Symposium on Computers and Communications (ISCC), pages 1–6. IEEE.
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.
Conforti, L., Virdis, A., Puliafito, C., and Mingozzi, E. (2021). Extending the quic protocol to support live container migration at the edge. In 2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM), pages 61–70. IEEE.
Das, R. and Sidhanta, S. (2023). Live migration of containers in the edge. SN Computer Science, 4(5):479.
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.
Feitosa, L., Barbosa, V., Sabino, A., Lima, L. N., Fé, I., Silva, B., and Silva, F. A. (2024). Uma comparação de múltiplas políticas de migração de contêineres suportadas pela ferramenta criu. In Simpósio Brasileiro de Redes de Computadores e Sistemas Distribuídos (SBRC), pages 742–755. SBC.
Feitosa, L., Barbosa, V., Sabino, A., Lima, L. N., Fé, I., Silva, L. G., Callou, G., Carvalho, J., Leão, E., Nguyen, T. A., et al. (2025). A comprehensive performance evaluation of container migration strategies. Computing, 107(2):1–39.
Feitosa, L., Rego, P. A., and Silva, F. A. (2023). Avaliaçao de desempenho de migraçao ao vivo de contêineres com redes de petri estocásticas. In Workshop de Testes e Tolerância a Falhas (WTF), pages 94–107. SBC.
González, A. E. and Arzuaga, E. (2020). Herdmonitor: monitoring live migrating containers in cloud environments. In 2020 IEEE International Conference on Big Data (Big Data), pages 2180–2189. IEEE.
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.
Junior, P. S., Miorandi, D., and Pierre, G. (2020). Stateful container migration in geo-distributed environments. In 2020 IEEE International Conference on Cloud Computing Technology and Science (CloudCom), pages 49–56. IEEE.
Kakakhel, S. R. U., Mukkala, L., Westerlund, T., and Plosila, J. (2018). Virtualization at the network edge: A technology perspective. In 2018 Third International Conference on Fog and Mobile Edge Computing (FMEC), pages 87–92. 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.
Kotikalapudi, S. V. N. (2017). Comparing live migration between linux containers and kernel virtual machine: investigation study in terms of parameters.
Ma, L., Yi, S., Carter, N., and Li, Q. (2018). Efficient live migration of edge services leveraging container layered storage. IEEE Transactions on Mobile Computing, 18(9):2020–2033.
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.
Majeed, A. A., Kilpatrick, P., Spence, I., and Varghese, B. (2020). Modelling fog offloading performance. In 2020 IEEE 4th International Conference on Fog and Edge Computing (ICFEC), pages 29–38. IEEE.
Malhotra, M. and Trivedi, K. S. (1995). Dependability modeling using petri-nets. IEEE Transactions on Reliability, 44(3):428–440.
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.
Pickartz, S., Eiling, N., Lankes, S., Razik, L., and Monti, A. (2016). Migrating linux containers using criu. In High Performance Computing: ISC High Performance 2016 International Workshops, pages 674–684. Springer.
Ramanathan, S., Kondepu, K., Razo, M., Tacca, M., Valcarenghi, L., and Fumagalli, A. (2021a). Live migration of virtual machine and container based mobile core network components: A comprehensive study. IEEE Access, 9:105082–105100.
Ramanathan, S., Kondepu, K., Zhang, T., Mirkhanzadeh, B., Razo, M., Tacca, M., Valcarenghi, L., and Fumagalli, A. (2021b). A comprehensive study of virtual machine and container based core network components migration in openroadm sdn-enabled network. arXiv preprint arXiv:2108.12509.
Requeno, J.-I., Merseguer, J., and Bernardi, S. (2017). Performance analysis of apache storm applications using stochastic petri nets. In 2017 IEEE International Conference on Information Reuse and Integration (IRI), pages 411–418. IEEE.
Silva, F. A., Fé, I., and Gonçalves, G. (2021). Stochastic models for performance and cost analysis of a hybrid cloud and fog architecture. The Journal of Supercomputing, 77(2):1537–1561.
Smimite, O. and Afdel, K. (2019). Impact of hybrid virtualization using vm and container on live migration and cloud performance. In Lecture Notes in Real-Time Intelligent Systems, pages 196–208. Springer.
Statista (2023). Container technology - statistics and facts.
Stoyanov, R. and Kollingbaum, M. J. (2018). Efficient live migration of linux containers. In High Performance Computing: ISC High Performance 2018 International Workshops, pages 184–193. Springer.
Tay, Y., Gaurav, K., and Karkun, P. (2017). A performance comparison of containers and virtual machines in workload migration context. In 2017 IEEE 37th International Conference on Distributed Computing Systems Workshops (ICDCSW), pages 61–66. IEEE.
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.
Turnbull, J. (2014). The Docker Book: Containerization is the new virtualization. James Turnbull, San Francisco, CA.
Varasteh, A. and Goudarzi, M. (2015). Server consolidation techniques in virtualized data centers: A survey. IEEE Systems Journal, 11(2):772–783.
Vaughan-Nichols, S. (2022). Migrating from VMware to OpenStack: Optimizing your Infrastructure to Save Money and Avoid Vendor-Lock-in. Acessado em: 2 de novembro de 2024.
Xu, B., Wu, S., Xiao, J., Jin, H., Zhang, Y., Shi, G., Lin, T., Rao, J., Yi, L., and Jiang, J. (2020). Sledge: Towards efficient live migration of docker containers. In 2020 IEEE 13th International Conference on Cloud Computing (CLOUD), pages 321–328. IEEE.
Publicado
19/05/2025
Como Citar
FEITOSA, Leonel; REGO, Paulo; SILVA, Francisco Airton.
Container Migration Performance Evaluation: An Approach Based on Stochastic Petri Nets. In: CONCURSO DE TESES E DISSERTAÇÕES - SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 43. , 2025, Natal/RN.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 272-281.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc_estendido.2025.7205.
