Caracterização de Mobilidade e Detecção de Comunidades baseadas em Tópicos de Interesse
Resumo
Redes móveis ad hoc impõem desafios como estabelecimento de conexões, descoberta de rotas e duração da rede devido à mobilidade dos nodos. Nesse sentido, pesquisadores vem analisando aspectos de mobilidade, p.ex., tempo de contato e entre-contato dos dispositivos e as comunidades formadas, em cenários como campus universitário, veículos e em conferências. Este trabalho caracteriza a mobilidade de participantes de uma conferência e propõe a detecção de comunidades baseadas em tópicos de interesse. Os dados usados nesse estudo, coletados durante o SBRC 2019 por meio de um app de gamificação, foram anonimizados e modelados como um grafo temporal. Os resultados mostram que, embora cada participante tenha um alto número de contatos, o tempo de contato é baixo. Além disso, as comunidades detectadas a partir dos tópicos de interesse são similares aos k-cliques do grafo temporal.
Palavras-chave:
Computação urbana, Redes móveis, Redes sociais
Referências
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Awuor, F. M., Wang, C.-Y., and Tsai, T.-C. (2018). Motivating content sharing and trustworthiness in mobile social networks. IEEE Access, 6:28339–28355.
Dede, J., Förster, A., Hernández-Orallo, E., Herrera-Tapia, J., Kuladinithi, K., Kuppusamy, V., Manzoni, P., bin Muslim, A., Udugama, A., and Vatandas, Z. (2017). Simulating opportunistic networks: Survey and future directions. IEEE Communications Surveys & Tutorials, 20(2):1547–1573.
Höyhtyä, M., Apilo, O., and Lasanen, M. (2018). Review of latest advances in 3gpp standardization: D2d communication in 5g systems and its energy consumption models. Future Internet, 10(1):3.
Marques-Neto, H. T., Xavier, F. H., Xavier, W. Z., Malab, C. H. S., Ziviani, A., Silveira, L. M., and Almeida, J. M. (2018). Understanding human mobility and workload dynamics due to different large-scale events using mobile phone data. Journal of Network and Systems Management, 26(4):1079–1100.
McGeehan, D., Madria, S., and Lin, D. (2019). Effective social-context based message delivery using chitchat in sparse delay tolerant networks. Distributed and Parallel Databases, pages 1–38.
Mota, V. F., Cunha, F. D., Macedo, D. F., Nogueira, J. M., and Loureiro, A. A. (2014). Protocols, mobility models and tools in opportunistic networks: A survey. Computer Communications, 48:5–19.
Nguyen, N. P., Dinh, T. N., Tokala, S., and Thai, M. T. (2011). Overlapping communities in dynamic networks: their detection and mobile applications. In 17th Int’l conference on Mobile computing and networking, pages 85–96. ACM.
Palla, G., Derényi, I., Farkas, I., and Vicsek, T. (2005). Uncovering the overlapping community structure of complex networks in nature and society. nature, 435(7043):814.
Pietilänen, A.-K. and Diot, C. (2012). Dissemination in opportunistic social networks: The role of temporal communities. In Symposium on Mobile Ad Hoc Networking and Computing, pages 165–174, New York, NY, USA. ACM.
Trifunovic, S., Kouyoumdjieva, S. T., Distl, B., Pajevic, L., Karlsson, G., and Plattner, B. (2017). A decade of research in opportunistic networks: challenges, relevance, and future directions. IEEE Communications Magazine, 55(1):168–173.
Viard, J., Latapy, M., and Magnien, C. (2015). Revealing contact patterns among high-school students using maximal cliques in link streams. In Conference on Advances in Social Networks Analysis and Mining, pages 1517–1522. IEEE.
Wang, R., Yang, H., Wang, H., and Wu, D. (2016). Social overlapping community-aware neighbor discovery for d2d communications. IEEE Wireless Communications, 23(4):28–34.
Whitbeck, J., Dias de Amorim, M., Conan, V., and Guillaume, J.-L. (2012). Temporal reachability graphs. In Proceedings of the 18th annual international conference on Mobile computing and networking, pages 377–388. ACM.
Wu, J., Chen, Z., and Zhao, M. (2019). Information cache management and data transmission algorithm in opportunistic social networks. Wireless networks, 25(6):2977–2988.
Xu, H., Hu, Y., Wang, Z., Ma, J., and Xiao, W. (2013). Core-based dynamic community detection in mobile social networks. Entropy, 15(12):5419–5438.
Zhao, Y. and Song, W. (2017). Survey on social-aware data dissemination over mobile wireless networks. IEEE Access, 5:6049–6059.
Appel, A. P., Cunha, R. L. F., Aggarwal, C. C., and Terakado, M. M. (2019). Temporally evolving community detection and prediction in content-centric networks. In Machine Learning and Knowledge Discovery in Databases, pages 3–18, Cham. Springer International Publishing.
Awuor, F. M., Wang, C.-Y., and Tsai, T.-C. (2018). Motivating content sharing and trustworthiness in mobile social networks. IEEE Access, 6:28339–28355.
Dede, J., Förster, A., Hernández-Orallo, E., Herrera-Tapia, J., Kuladinithi, K., Kuppusamy, V., Manzoni, P., bin Muslim, A., Udugama, A., and Vatandas, Z. (2017). Simulating opportunistic networks: Survey and future directions. IEEE Communications Surveys & Tutorials, 20(2):1547–1573.
Höyhtyä, M., Apilo, O., and Lasanen, M. (2018). Review of latest advances in 3gpp standardization: D2d communication in 5g systems and its energy consumption models. Future Internet, 10(1):3.
Marques-Neto, H. T., Xavier, F. H., Xavier, W. Z., Malab, C. H. S., Ziviani, A., Silveira, L. M., and Almeida, J. M. (2018). Understanding human mobility and workload dynamics due to different large-scale events using mobile phone data. Journal of Network and Systems Management, 26(4):1079–1100.
McGeehan, D., Madria, S., and Lin, D. (2019). Effective social-context based message delivery using chitchat in sparse delay tolerant networks. Distributed and Parallel Databases, pages 1–38.
Mota, V. F., Cunha, F. D., Macedo, D. F., Nogueira, J. M., and Loureiro, A. A. (2014). Protocols, mobility models and tools in opportunistic networks: A survey. Computer Communications, 48:5–19.
Nguyen, N. P., Dinh, T. N., Tokala, S., and Thai, M. T. (2011). Overlapping communities in dynamic networks: their detection and mobile applications. In 17th Int’l conference on Mobile computing and networking, pages 85–96. ACM.
Palla, G., Derényi, I., Farkas, I., and Vicsek, T. (2005). Uncovering the overlapping community structure of complex networks in nature and society. nature, 435(7043):814.
Pietilänen, A.-K. and Diot, C. (2012). Dissemination in opportunistic social networks: The role of temporal communities. In Symposium on Mobile Ad Hoc Networking and Computing, pages 165–174, New York, NY, USA. ACM.
Trifunovic, S., Kouyoumdjieva, S. T., Distl, B., Pajevic, L., Karlsson, G., and Plattner, B. (2017). A decade of research in opportunistic networks: challenges, relevance, and future directions. IEEE Communications Magazine, 55(1):168–173.
Viard, J., Latapy, M., and Magnien, C. (2015). Revealing contact patterns among high-school students using maximal cliques in link streams. In Conference on Advances in Social Networks Analysis and Mining, pages 1517–1522. IEEE.
Wang, R., Yang, H., Wang, H., and Wu, D. (2016). Social overlapping community-aware neighbor discovery for d2d communications. IEEE Wireless Communications, 23(4):28–34.
Whitbeck, J., Dias de Amorim, M., Conan, V., and Guillaume, J.-L. (2012). Temporal reachability graphs. In Proceedings of the 18th annual international conference on Mobile computing and networking, pages 377–388. ACM.
Wu, J., Chen, Z., and Zhao, M. (2019). Information cache management and data transmission algorithm in opportunistic social networks. Wireless networks, 25(6):2977–2988.
Xu, H., Hu, Y., Wang, Z., Ma, J., and Xiao, W. (2013). Core-based dynamic community detection in mobile social networks. Entropy, 15(12):5419–5438.
Zhao, Y. and Song, W. (2017). Survey on social-aware data dissemination over mobile wireless networks. IEEE Access, 5:6049–6059.
Publicado
07/12/2020
Como Citar
RIBEIRO, Iran; CASTANHEIRA, Lucas; SCHAEFFER-FILHO, Alberto; CORDEIRO, Weverton; MOTA, Vinícius.
Caracterização de Mobilidade e Detecção de Comunidades baseadas em Tópicos de Interesse. In: SIMPÓSIO BRASILEIRO DE REDES DE COMPUTADORES E SISTEMAS DISTRIBUÍDOS (SBRC), 38. , 2020, Rio de Janeiro.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2020
.
p. 603-616.
ISSN 2177-9384.
DOI: https://doi.org/10.5753/sbrc.2020.12312.
