Vehicle Cooperation Based on Social Characteristics for Data Dissemination of Urban Critical Events

• Alisson Yury Dutra de Medeiros Federal University of Paraíba (UFPB)
• José Everaldo Andrade Júnior Federal University of Paraíba (UFPB)
• Aldri Luiz dos Santos Federal University of Paraná (UFPR)
• Fernando de Menezes Matos Federal University of Paraíba (UFPB)

DOI: https://doi.org/10.5753/courb.2020.12359

Abstract

Critical urban events need to be efficiently handled, for instance, through rapid notification. Vehicular Ad Hoc Networks (VANETs) are a promising choice in supporting notification of information on arbitrary critical events. Although the dynamicity of VANETs compromises the dissemination process, the connections among vehicles based on the users' social interests allow for optimizing message exchange and data dissemination. This paper introduces SOCIABLE, a robust data dissemination system for critical urban events that operates in a SIoV network. It is based on vehicles' community with common interests and/or similar routines and employs social influence of vehicles according to their network location to select relay vehicles. In a comparative analysis on NS3 with the MINUET system, SOCIABLE achieved 36.56% less messages in a dense VANET and a maximum delay of 0.028s in a sparse VANET, delivering critical event data in a real-time and robust way without overloading the network.

Keywords: SIoV, Critical Events, Recognition, Social Influence

References

Akabane, A. T., Immich, R., Madeira, E. R., and Villas, L. A. (2019). IMOB: An Intelligent Urban Mobility Management System Based on Vehicular Social Networks. In IEEE Vehicular Networking Conference, VNC, volume 2018-Decem.

Andrade, J. E., Veloso, K., Silva, N. d. V., dos Santos, A. L., and Matos, F. M. (2019). Monitoramento e Disseminação Cooperativa de Eventos Emergenciais Apoiado por Agrupamentos de Veículos. In Anais do Workshop de Gerência e Operação de Redes e Serviços, pages 127-140.

Bonacich, P. (1987). Power and centrality: A family of measures. American Journal of Sociology, 92(5):1170-1182.

Campolo, C., Molinaro, A., and Tera, A. (2018). A reference framework for social-enhanced Vehicle-to-Everything communications in 5G scenarios. Computer Networks, 143:140-152.14

Cunha, F. D., Maia, G., Viana, A. C., Mini, R. A., Villas, L. A., and Loureiro, A. A. (2014). Socially inspired data dissemination for Vehicular Ad Hoc Networks. MSWiM 2014 - Proceedingsof the 17th ACM International Conference on Modeling, Analysis and Simulation of Wireless and Mobile Systems, pages 81-85.

Freeman, L. C. (1978). Centrality in social networks conceptual clarification. Social Networks,1(3):215 — 239.

Khan, S. and Franzle, M. (2015). Robust mid-range communication in Urban VANETS. In International Conference on Advanced Communication Technology, ICACT, pages 115-120.

Monreal, C. O. (2018). Future urban mobility group: Smart cities research institute swinburne university of technology, Melbourne Australia. IEEE Intelligent Transportation Systems Magazine, 10(2):203-205.

Nagaraj, K., Bhasale, S. S., McNair, J., and Helmy, A. (2019). Vulnerability assessment and classification based on influence metrics in mobile social networks. In Proceedings of the 17th ACM International Symposium on Mobility Management and Wireless Access, MobiWac "19,page 9-16, New York, NY, USA. Association for Computing Machinery.

Rahim, A., Kong, X., Xia, F., Ning, Z., Ullah, N., Wang, J., and Das, S. K. (2018). Vehicular Social Networks: A survey. Pervasive and Mobile Computing, 43:96-113.

Rahim, A., Ma, K., Zhao, W., Tolba, A., Al-Makhadmeh, Z., and Xia, F. (2018b). Cooperativedata forwarding based on crowdsourcing in vehicular social networks. Pervasive and Mobile Computing, 51:43-55.

Shrestha, R., Bajracharya, R., and Nam, S. Y. (2018). Centralized approach for trustworthy message dissemination in VANET. In IEEE/IFIP Network Operations and Management Symposium: Cognitive Management in a Cyber World, NOMS 2018, pages 1-5.

Silva, R. and Igbal, R. (2019). Ethical Implications of Social Internet of Vehicles Systems. IEEE Internet of Things Journal, 6(1):517-531.

Vegni, A.M. and Loscrí, V. (2015). A survey on vehicular social networks. IEEE Communications Surveys and Tutorials, 17(4):2397-2419.

Wang, X., Ning, Z., Hu, X., Ngai, E. C., Wang, L., Hu, B., and Kwok, R. Y. (2018). A City-Wide Real-Time Traffic Management System: Enabling Crowdsensing in Social Internet of Vehicles. IEEE Communications Magazine, 56(9):19-25.

Wang, X., Ning, Z., Zhou, M. C., Hu, X., Wang, L., Zhang, Y., Yu, F. R., and Hu, B. (2019). Privacy-Preserving Content Dissemination for Vehicular Social Networks: Challenges and Solutions. IEEE Communications Surveys and Tutorials, 21(2):1314-1345.

Wu, F.-J. and Solmaz, G. (2019). CrowdEstimator: Approximating Crowd Sizes with Multi-modal Data for Internet-of-Things Services. In MobiSys 2018 - Proceedings of the 16th ACM International Conference on Mobile Systems, Applications, and Services, pages 337-349.

Xu, W., Guo, S., Zhou, H., Ma, S., and Wu, M. (2019). A Queueing Analysis of the Opportunistic Vehicle-to-Vehicle Communication. In IEEE Global Comm. Conference, pages 25-30.

Yaqub, M. A., Ahmed, S. H., Bouk, S. H., and Kim, D. (2018). Enabling critical content dissemination in vehicular named data networks. In Proceedings of the 2018 Research in Adaptive and Convergent Systems, RACS 2018, pages 94-99. Association for Computing Machinery, Inc.