Computational Capacity Planning for Running Multiplayer Games on Cloud and Fog Infrastructures
Resumo
Introduction: Data traffic in multiplayer games consists of realtime exchanges of commands between servers and players’ devices, which demand an immediate response. As the data volume increases, the system becomes overloaded, resulting in high latency and packet loss. Objective: This work proposes a new Stochastic Petri Net (SPN) model to evaluate the performance of this traffic in Fog–Cloud architectures designed for large-scale multiplayer games. Methodology: We built a SPN model and validated a simplified version; the model computes utilization, mean response time, drop probability, and throughput, allowing us to analyze the impact of different capacity configurations and load-distribution strategies. Results: The results reveal a direct relationship among processing capacity, load balancing, and quality of service: increasing the number of cloud GPUs reduces latency and packet loss while boosting throughput.
Palavras-chave:
Stochastic Petri Nets, Multiplayer Games, Fog–Cloud Computing, Performance Modeling, Capacity Planning
Referências
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Benamer, A.-R., Hadj-Alouane, N. B., Boussetta, K., e Hadj-Alouane, A. B. (2024). A genetic algorithm-based approach for placement in the fog of latency-sensitive multiplayer game servers. Cluster Computing.
Cheng, D., Verma, R., Rane, D., Jha, R. S., e Ibrahim, W. (2022). Next-generation optimization models and algorithms in cloud and fog computing virtualization security: The present state and future. Scientific Programming, 2022:2419291.
Hains, G., Mazur, C., Ayers, J., Humphrey, J., Khmelevsky, Y., e Sutherland, T. (2020). The wtfast’s gamers private network (gpn ®) performance evaluation results. In 2020 IEEE International Systems Conference (SysCon), pages 1–6.
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Kinzhalin, A., Kohn, R., Lombard, D., e Morin, R. (2011). Enabling dynamic data centers with a smart bare-metal server platform. Cluster Computing, 14(3):245–258.
Little, J. D. C. (1961). A proof for the queuing formula. Operations Research, 9(3):383– 387.
Maciel, P., Matos, R., Silva, B., Figueiredo, J., Oliveira, D., Fé, I., Maciel, R., e 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.
Malta, E. M., Avila, S., e Borin, E. (2019). Exploring the cost-benefit of aws ec2 gpu instances for deep learning applications. In Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing (UCC), pages 21–29. IEEE.
Moon, D. (2024). Network traffic characteristics and analysis in recent mobile games. Applied Sciences, 14(4).
Newzoo (2024). Global games market report 2024. Accessed: November 21, 2024.
Olliaro, D., Mancuso, V., Castagno, P., Sereno, M., e Marsan, M. A. (2024). Gaming on the edge: Performance issues of distributed online gaming. In 2024 IFIP Networking Conference (IFIP Networking), pages 259–267.
Ostermann, S., Iosup, A., Yigitbasi, N., Prodan, R., Fahringer, T., e Epema, D. (2009). A performance analysis of ec2 cloud computing services for scientific computing. In Cloud Computing, volume 5931 of Lecture Notes in Computer Science, pages 115– 131. Springer.
Rossi, H. S., Mitra, K., Åhlund, C., Cotanis, I., Örgen, N., e Johansson, P. (2024). Objective qoe models for cloud-based first person shooter game over mobile networks. In 2024 IEEE 21st Consumer Communications and Networking Conference (CCNC), pages 550–553.
Saldana, J., Suznjevic, M., Sequeira, L., Fernandez-Navajas, J., Matijasevic, M., e Ruiz-Mas, J. (2012). The effect of tcp variants on the coexistence of mmorpg and best-effort traffic. In 2012 21st International Conference on Computer Communications and Networks (ICCCN), page 1–5. IEEE.
Wong, A., Chiu, C., Hains, G., Behnke, J., Khmelevsky, Y., e Mazur, C. (2021). Modelling network latency and online video gamers’ satisfaction with machine learning. In 2021 IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE), pages 1–5.
Benamer, A.-R., Hadj-Alouane, N. B., Boussetta, K., e Hadj-Alouane, A. B. (2024). A genetic algorithm-based approach for placement in the fog of latency-sensitive multiplayer game servers. Cluster Computing.
Cheng, D., Verma, R., Rane, D., Jha, R. S., e Ibrahim, W. (2022). Next-generation optimization models and algorithms in cloud and fog computing virtualization security: The present state and future. Scientific Programming, 2022:2419291.
Hains, G., Mazur, C., Ayers, J., Humphrey, J., Khmelevsky, Y., e Sutherland, T. (2020). The wtfast’s gamers private network (gpn ®) performance evaluation results. In 2020 IEEE International Systems Conference (SysCon), pages 1–6.
Incorporated, S. (2019). The global internet phenomena report: Q3 2019. Accessed: November 23, 2024.
Kinzhalin, A., Kohn, R., Lombard, D., e Morin, R. (2011). Enabling dynamic data centers with a smart bare-metal server platform. Cluster Computing, 14(3):245–258.
Little, J. D. C. (1961). A proof for the queuing formula. Operations Research, 9(3):383– 387.
Maciel, P., Matos, R., Silva, B., Figueiredo, J., Oliveira, D., Fé, I., Maciel, R., e 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.
Malta, E. M., Avila, S., e Borin, E. (2019). Exploring the cost-benefit of aws ec2 gpu instances for deep learning applications. In Proceedings of the 12th IEEE/ACM International Conference on Utility and Cloud Computing (UCC), pages 21–29. IEEE.
Moon, D. (2024). Network traffic characteristics and analysis in recent mobile games. Applied Sciences, 14(4).
Newzoo (2024). Global games market report 2024. Accessed: November 21, 2024.
Olliaro, D., Mancuso, V., Castagno, P., Sereno, M., e Marsan, M. A. (2024). Gaming on the edge: Performance issues of distributed online gaming. In 2024 IFIP Networking Conference (IFIP Networking), pages 259–267.
Ostermann, S., Iosup, A., Yigitbasi, N., Prodan, R., Fahringer, T., e Epema, D. (2009). A performance analysis of ec2 cloud computing services for scientific computing. In Cloud Computing, volume 5931 of Lecture Notes in Computer Science, pages 115– 131. Springer.
Rossi, H. S., Mitra, K., Åhlund, C., Cotanis, I., Örgen, N., e Johansson, P. (2024). Objective qoe models for cloud-based first person shooter game over mobile networks. In 2024 IEEE 21st Consumer Communications and Networking Conference (CCNC), pages 550–553.
Saldana, J., Suznjevic, M., Sequeira, L., Fernandez-Navajas, J., Matijasevic, M., e Ruiz-Mas, J. (2012). The effect of tcp variants on the coexistence of mmorpg and best-effort traffic. In 2012 21st International Conference on Computer Communications and Networks (ICCCN), page 1–5. IEEE.
Wong, A., Chiu, C., Hains, G., Behnke, J., Khmelevsky, Y., e Mazur, C. (2021). Modelling network latency and online video gamers’ satisfaction with machine learning. In 2021 IEEE International Conference on Recent Advances in Systems Science and Engineering (RASSE), pages 1–5.
Publicado
30/09/2025
Como Citar
ALVES, Melissa; WANDERLEI, Jose; BARBOSA, Vandirleya; SABINO, Arthur; LIMA, Luiz Nelson; FEITOSA, Leonel; CLUA, Esteban; SILVA, Francisco Airton.
Computational Capacity Planning for Running Multiplayer Games on Cloud and Fog Infrastructures. In: SIMPÓSIO BRASILEIRO DE JOGOS E ENTRETENIMENTO DIGITAL (SBGAMES), 24. , 2025, Salvador/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2025
.
p. 516-525.
DOI: https://doi.org/10.5753/sbgames.2025.9829.
