Um Simulador de Eventos Discretos Multiagentes Distribuído
Resumo
Este trabalho propõe um simulador de eventos discretos multiagentes, projetado para memória compartilhada e distribuída, focado em lidar com cenários de larga escala com balanceamento de carga eficiente. Resultados mostram a execução de cenários com mais de 4 milhões de agentes em 3,5 h (memória compartilhada) e 9,5 h (memória distribuída).Referências
Alvarez Lopez, P., Behrisch, M., Bieker-Walz, L., Erdmann, J., Flötteröd, Y.-P., Hilbrich, R., Lücken, L., Rummel, J., Wagner, P., and Wießner, E. (2018). Microscopic traffic simulation using sumo. In 2019 IEEE Intelligent Transportation Systems Conference (ITSC), pages 2575–2582. IEEE.
Babulak, E. and Wang, M. (2010). Discrete event simulation. Aitor Goti (Hg.): Discrete Event Simulations. Rijeka, Kroatien: Sciyo, page 1.
Bellini, P., Palesi, L. A. I., Mereu, F., and Nesi, P. (2025). Scalable framework for behavior execution of mobility and transport digital twins. In 2025 IEEE 11th International Conference on Big Data Computing Service and Machine Learning Applications (Big-DataService), pages 1–9. IEEE.
Clemen, T., Ahmady-Moghaddam, N., Lenfers, U. A., Ocker, F., Osterholz, D., Ströbele, J., and Glake, D. (2021). Multi-agent systems and digital twins for smarter cities. In Proceedings of the 2021 ACM SIGSIM conference on principles of advanced discrete simulation, pages 45–55.
Lohman, W., Cornelissen, H., Borst, J., Klerkx, R., Araghi, Y., and Walraven, E. (2023). Building digital twins of cities using the inter model broker framework. Future Generation Computer Systems, 148:501–513.
Mavromatis, I., Piechocki, R. J., Sooriyabandara, M., and Parekh, A. (2020). Drive: A digital network oracle for cooperative intelligent transportation systems. In 2020 IEEE Symposium on Computers and Communications (ISCC), pages 1–7. IEEE.
Santana, E. F. Z., Lago, N., Kon, F., and Milojicic, D. S. (2018). Interscsimulator: Large-scale traffic simulation in smart cities using erlang. In Multi-Agent Based Simulation XVIII: International Workshop, MABS 2017, São Paulo, Brazil, May 8-12, 2017, Revised Selected Papers 18, pages 211–227. Springer.
Schuhmann, F., Nguyen, N. A., Schweizer, J., Huang, W.-C., and Lienkamp, M. (2024). Creating and validating hybrid large-scale, multi-modal traffic simulations for efficient transport planning. Smart Cities, 8(1):2.
Shukla, P. R. et al. (2022). Climate change 2022: Mitigation of climate change. Contribution of working group III to the sixth assessment report of the Intergovernmental Panel on Climate Change, 10:9781009157926.
Van Den Berghe, S. (2021). A processing architecture for real-time predictive smart city digital twins. In 2021 IEEE International Conference on Big Data (Big Data), pages 2867–2874. IEEE.
W Axhausen, K., Horni, A., and Nagel, K. (2016). The multi-agent transport simulation MATSim. Ubiquity Press.
Yeon, H., Eom, T., Jang, K., and Yeo, J. (2023). Dtumos, digital twin for large-scale urban mobility operating system. Scientific Reports, 13(1):5154.
Babulak, E. and Wang, M. (2010). Discrete event simulation. Aitor Goti (Hg.): Discrete Event Simulations. Rijeka, Kroatien: Sciyo, page 1.
Bellini, P., Palesi, L. A. I., Mereu, F., and Nesi, P. (2025). Scalable framework for behavior execution of mobility and transport digital twins. In 2025 IEEE 11th International Conference on Big Data Computing Service and Machine Learning Applications (Big-DataService), pages 1–9. IEEE.
Clemen, T., Ahmady-Moghaddam, N., Lenfers, U. A., Ocker, F., Osterholz, D., Ströbele, J., and Glake, D. (2021). Multi-agent systems and digital twins for smarter cities. In Proceedings of the 2021 ACM SIGSIM conference on principles of advanced discrete simulation, pages 45–55.
Lohman, W., Cornelissen, H., Borst, J., Klerkx, R., Araghi, Y., and Walraven, E. (2023). Building digital twins of cities using the inter model broker framework. Future Generation Computer Systems, 148:501–513.
Mavromatis, I., Piechocki, R. J., Sooriyabandara, M., and Parekh, A. (2020). Drive: A digital network oracle for cooperative intelligent transportation systems. In 2020 IEEE Symposium on Computers and Communications (ISCC), pages 1–7. IEEE.
Santana, E. F. Z., Lago, N., Kon, F., and Milojicic, D. S. (2018). Interscsimulator: Large-scale traffic simulation in smart cities using erlang. In Multi-Agent Based Simulation XVIII: International Workshop, MABS 2017, São Paulo, Brazil, May 8-12, 2017, Revised Selected Papers 18, pages 211–227. Springer.
Schuhmann, F., Nguyen, N. A., Schweizer, J., Huang, W.-C., and Lienkamp, M. (2024). Creating and validating hybrid large-scale, multi-modal traffic simulations for efficient transport planning. Smart Cities, 8(1):2.
Shukla, P. R. et al. (2022). Climate change 2022: Mitigation of climate change. Contribution of working group III to the sixth assessment report of the Intergovernmental Panel on Climate Change, 10:9781009157926.
Van Den Berghe, S. (2021). A processing architecture for real-time predictive smart city digital twins. In 2021 IEEE International Conference on Big Data (Big Data), pages 2867–2874. IEEE.
W Axhausen, K., Horni, A., and Nagel, K. (2016). The multi-agent transport simulation MATSim. Ubiquity Press.
Yeon, H., Eom, T., Jang, K., and Yeo, J. (2023). Dtumos, digital twin for large-scale urban mobility operating system. Scientific Reports, 13(1):5154.
Publicado
02/09/2026
Como Citar
ROCHA, Francisco Wallison; FRANCESQUINI, Emilio; CORDEIRO, Daniel.
Um Simulador de Eventos Discretos Multiagentes Distribuído. In: ESCOLA REGIONAL DE ALTO DESEMPENHO DE SÃO PAULO (ERAD-SP), 17. , 2026, São Paulo/SP.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 9-12.
DOI: https://doi.org/10.5753/eradsp.2026.30764.
