Em Direção ao Realismo Espacial: Um Modelo de Mobilidade Humana Baseado em Small World In Motion e OpenStreetMap
Resumo
Modelos de mobilidade humana desempenham um papel fundamental na avaliação de redes móveis e oportunísticas, influenciando diretamente padrões de conectividade e desempenho de protocolos. Embora modelos sintéticos ofereçam simplicidade e escalabilidade, eles frequentemente desconsideram restrições espaciais reais, enquanto abordagens baseadas em mapas ou traços reais aumentam o realismo à custa de maior complexidade e menor reprodutibilidade. Este artigo propõe o modelo SWIM-OSM, uma extensão do modelo Small World In Motion (SWIM) que incorpora restrições espaciais a partir de dados do OpenStreetMap. O modelo preserva os princípios centrais do SWIM, combinando proximidade e popularidade dos destinos, ao mesmo tempo em que restringe o movimento dos nós a grafos urbanos reais. Resultados experimentais obtidos com o simulador The ONE indicam que o SWIM-OSM produz métricas de mobilidade e desempenho de rede mais realistas e conservadoras quando comparado a modelos puramente sintéticos, configurando-se como uma alternativa equilibrada para simulações de redes oportunísticas em ambientes urbanos.Referências
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Coelho, J. V. S., Lausberg, L. L., Zißner, P., Sevenich, P., Mota, V. F. S., Prazeres, C. V. S., Rettore, P. H. L., and Santos, B. P. (2025). SnapAI: A Simulator for Network Algorithms and Protocols with Artificial Intelligence Integration. In Proceedings of the 12th International Conference on Software Defined Systems (SDS 2025), Lyon, France. IEEE.
Ekman, F., Keränen, A., Karvo, J., and Ott, J. (2008). Working day movement model. In Proceedings of the 1st ACM SIGMOBILE workshop on Mobility models, pages 33–40.
Keränen, A., Ott, J., and Kärkkäinen, T. (2009). The ONE simulator for DTN protocol evaluation. In Proceedings of the 2nd international conference on simulation tools and techniques, pages 1–10.
Kosta, S., Mei, A., and Stefa, J. (2010). Small world in motion (SWIM): Modeling communities in ad-hoc mobile networking. In 2010 7th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), pages 1–9. IEEE.
Kumar, A. A., Rao, S., and Goswami, D. (2013). Ns3 simulator for a study of data center networks. In 2013 IEEE 12th International Symposium on Parallel and Distributed Computing, pages 224–231. IEEE.
Lee, K., Hong, S., Kim, S. J., Rhee, I., and Chong, S. (2011). SLAW: Self-similar least-action human walk. IEEE/ACM Transactions On Networking, 20(2):515–529.
Munjal, A., Camp, T., and Navidi, W. C. (2011). Smooth: a simple way to model human mobility. In Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems, pages 351–360.
Oikonomou, G., Duquennoy, S., Elsts, A., Eriksson, J., Tanaka, Y., and Tsiftes, N. (2022). The Contiki-NG open source operating system for next generation IoT devices. SoftwareX, 18:101089.
Rettore, P. H., Mast, J., Aurisch, T., Viana, A. C., Sevenich, P., and Santos, B. P. (2025). Military IoT from Management to Perception: Challenges and Opportunities Across Layers. IEEE Internet of Things Magazine, 8(2):25–31.
Rettore, P. H., Santos, B. P., Lopes, R. R. F., Maia, G., Villas, L. A., and Loureiro, A. A. (2020). Road data enrichment framework based on heterogeneous data fusion for ITS. IEEE transactions on intelligent transportation systems, 21(4):1751–1766.
Santos, B. P., Goussevskaia, O., Vieira, L. F., Vieira, M. A., and Loureiro, A. A. (2018). Mobile matrix: routing under mobility in IoT, IoMT, and social IoT. Ad Hoc Networks, 78:84–98.
Schwamborn, M. and Aschenbruck, N. (2013). Introducing geographic restrictions to the slaw human mobility model. In 2013 IEEE 21st international symposium on modelling, analysis and simulation of computer and telecommunication systems, pages 264–272. IEEE.
Solmaz, G. and Turgut, D. (2019). A survey of human mobility models. IEEE Access, 7:125711–125731.
Vukadinovic, V., Dreier, F., and Mangold, S. (2011). A simple framework to simulate the mobility and activity of theme park visitors. In Proceedings of the 2011 Winter Simulation Conference (WSC), pages 3248–3260. IEEE.
Zheng, Q., Hong, X., Liu, J., Cordes, D., and Huang, W. (2010). Agenda driven mobility modelling. International Journal of Ad Hoc and Ubiquitous Computing, 5(1):22–36.
Camp, T., Boleng, J., and Davies, V. (2002). A survey of mobility models for ad hoc network research. Wireless communications and mobile computing, 2(5):483–502.
Coelho, J. V. S., Lausberg, L. L., Zißner, P., Sevenich, P., Mota, V. F. S., Prazeres, C. V. S., Rettore, P. H. L., and Santos, B. P. (2025). SnapAI: A Simulator for Network Algorithms and Protocols with Artificial Intelligence Integration. In Proceedings of the 12th International Conference on Software Defined Systems (SDS 2025), Lyon, France. IEEE.
Ekman, F., Keränen, A., Karvo, J., and Ott, J. (2008). Working day movement model. In Proceedings of the 1st ACM SIGMOBILE workshop on Mobility models, pages 33–40.
Keränen, A., Ott, J., and Kärkkäinen, T. (2009). The ONE simulator for DTN protocol evaluation. In Proceedings of the 2nd international conference on simulation tools and techniques, pages 1–10.
Kosta, S., Mei, A., and Stefa, J. (2010). Small world in motion (SWIM): Modeling communities in ad-hoc mobile networking. In 2010 7th Annual IEEE Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks (SECON), pages 1–9. IEEE.
Kumar, A. A., Rao, S., and Goswami, D. (2013). Ns3 simulator for a study of data center networks. In 2013 IEEE 12th International Symposium on Parallel and Distributed Computing, pages 224–231. IEEE.
Lee, K., Hong, S., Kim, S. J., Rhee, I., and Chong, S. (2011). SLAW: Self-similar least-action human walk. IEEE/ACM Transactions On Networking, 20(2):515–529.
Munjal, A., Camp, T., and Navidi, W. C. (2011). Smooth: a simple way to model human mobility. In Proceedings of the 14th ACM international conference on Modeling, analysis and simulation of wireless and mobile systems, pages 351–360.
Oikonomou, G., Duquennoy, S., Elsts, A., Eriksson, J., Tanaka, Y., and Tsiftes, N. (2022). The Contiki-NG open source operating system for next generation IoT devices. SoftwareX, 18:101089.
Rettore, P. H., Mast, J., Aurisch, T., Viana, A. C., Sevenich, P., and Santos, B. P. (2025). Military IoT from Management to Perception: Challenges and Opportunities Across Layers. IEEE Internet of Things Magazine, 8(2):25–31.
Rettore, P. H., Santos, B. P., Lopes, R. R. F., Maia, G., Villas, L. A., and Loureiro, A. A. (2020). Road data enrichment framework based on heterogeneous data fusion for ITS. IEEE transactions on intelligent transportation systems, 21(4):1751–1766.
Santos, B. P., Goussevskaia, O., Vieira, L. F., Vieira, M. A., and Loureiro, A. A. (2018). Mobile matrix: routing under mobility in IoT, IoMT, and social IoT. Ad Hoc Networks, 78:84–98.
Schwamborn, M. and Aschenbruck, N. (2013). Introducing geographic restrictions to the slaw human mobility model. In 2013 IEEE 21st international symposium on modelling, analysis and simulation of computer and telecommunication systems, pages 264–272. IEEE.
Solmaz, G. and Turgut, D. (2019). A survey of human mobility models. IEEE Access, 7:125711–125731.
Vukadinovic, V., Dreier, F., and Mangold, S. (2011). A simple framework to simulate the mobility and activity of theme park visitors. In Proceedings of the 2011 Winter Simulation Conference (WSC), pages 3248–3260. IEEE.
Zheng, Q., Hong, X., Liu, J., Cordes, D., and Huang, W. (2010). Agenda driven mobility modelling. International Journal of Ad Hoc and Ubiquitous Computing, 5(1):22–36.
Publicado
25/05/2026
Como Citar
OLIVEIRA, Edgar S.; MENEGUETTE, Rodolfo; FIGUEIREIDO, Gustavo; PEIXOTO, Maycon; PRAZERES, Cássio; RETTORE, Paulo H. L.; SANTOS, Bruno.
Em Direção ao Realismo Espacial: Um Modelo de Mobilidade Humana Baseado em Small World In Motion e OpenStreetMap. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 44. , 2026, Praia do Forte/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2026
.
p. 687-700.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2026.19829.
