The treatment of mobile and simultaneous critical urban events requires effective actions by the appropriate authorities. Additionally it implies communication challenges in the speed and accuracy of their occurrence by the entities, as well as dealing with the dynamics and speed in these environments. Cooperative solutions with shared resources that address these challenges become a real option in helping to handle these events. This paper presents an evaluation of dynamic monitoring and collaborative dissemination supported by vehicular groups. It aims to analyze the impact of multiple mobile and fixed events in an urban environment on information propagation, considering barriers imposed by the events and the environment. Differently from other studies in the literature, this work takes into account both fixed and mobile events, as well as simultaneous events. NS-3 simulation results show that the evaluated system monitored at least 87% and 51.5% of the time for mobile and fixed events respectively, and delivered information over 77% and 50% of the time for those events, while average delay remains close to 0.3 s in most scenarios. The achieved results also reveal that a more continuous monitoring of the mobile events is highly dependent on the strategy used to select the collaborating vehicles surrounding the event. The main contribution of this work consists of the performance analysis of both fixed and mobile simultaneous events to support studies on how moving events impact on the dissemination and delivery of real-time data, and thus encouraging the development of new data dissemination protocols for VANETs.
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Zhang, N., Huang, H., & Su, B. (2016). Comprehensive analysis of information dissemination in disasters. Physica A: Statistical Mechanics and its Applications, 462, 846.
Costa, D. G., & de Oliveira, F. P. (2020). A prioritization approach for optimization of multiple concurrent sensing applications in smart cities. Future Generation Computer Systems, 108, 228.
Tang, Y., & Huang, S. (2019). Assessing seismic vulnerability of urban road networks by a bayesian network approach. Transportation Research Part D: Transport and Environment, 77, 390.
Cantillo, V., Macea, L. F., & Jaller, M. (2019). Assessing vulnerability of transportation networks for disaster response operations. Networks and Spatial Economics, 19(1), 243.
Tang, P., Xia, Q., & Wang, Y. (2019). Addressing cascading effects of earthquakes in urban areas from network perspective to improve disaster mitigation. International Journal of Disaster Risk Reduction, 35, 101065.
Amiri, I. S., Prakash, J., Balasaraswathi, M., Sivasankaran, V., Sundararajan, T. V. P., Hindia, M. H. D. N., et al. (2020). Dabpr: a large-scale internet of things-based data aggregation back pressure routing for disaster management. Wireless Networks, 26(4), 2353.
Ferranti, L., D’Oro, S., Bonati, L., Demirors, E., Cuomo, F., & Melodia, T. (2019). Hiro-net: Self-organized robotic mesh networking for internet sharing in disaster scenarios. In 2019 IEEE 20th International Symposium on “A World of Wireless, Mobile and Multimedia Networks” (WoWMoM) (pp. 1–9).
Immich, R., Cerqueira, E., & Curado, M. (2019). Efficient high-resolution video delivery over vanets. Wireless Networks, 25(5), 2587.
Hilal, N., & Yurdakul, A. (2020). Model-based design of a roadside unit for emergency and disaster management. In NOMS 2020 - 2020 IEEE/IFIP Network Operations and Management Symposium (pp. 1–6).
Chou, Y.H., Chu, T.H., Kuo, S.Y., & Chen, C.Y. (2017). An adaptive emergency broadcast strategy for vehicular ad hoc networks. IEEE Sensors Journal 1–1.
Shah, S. A., et al. (2019). Towards disaster resilient smart cities: Can internet of things and big data analytics be the game changers? IEEE Access, 7, 91885.
Astarita, V., Giofré, V. P., Guido, G., Stefano, G., & Vitale, A. (2020). Mobile computing for disaster emergency management: Empirical requirements analysis for a cooperative crowdsourced system for emergency management operation. Smart Cities, 3(1), 31.
Boukerche, A. (2019). Smart disaster management and responses for smart cities: A new challenge for the next generation of distributed simulation systems. In 2019 IEEE/ACM 23rd International Symposium on Distributed Simulation and Real Time Applications (DS-RT) (pp. 1–2).
Nogueira, M., Arieta, F., Barabasz, L., & Santos, A. (2014). Mitigating flooding attacks on mobility in infrastructure-based vehicular networks. IEEE Latin America Transactions, 12(3), 475.
Shrestha, R., Bajracharya, R., Nam, S.Y. (2018). Centralized approach for trustworthy message dissemination in vanet. In IEEE/IFIP Network Operations and Management Symposium (NOMS) (pp. 1–5).
Li, Z., Song, Y., & Bi, J. (2019). Cadd: connectivity-aware data dissemination using node forwarding capability estimation in partially connected vanets. Wireless Networks, 25(1), 379.
Khakpour, S., Pazzi, R. W., & El-Khatib, K. (2017). Using clustering for target tracking in vehicular ad hoc networks. Vehicular Communications, 9, 83.
Kim, S. (2019). Effective crowdsensing and routing algorithms for next generation vehicular networks. Wireless Networks, 25(4), 1815.
Lee, M., & Atkison, T. (2020). Vanet applications: Past, present, and future, Vehicular Communications (p. 100310).
Trost, T., Trempler, M., Reußwig, A., & Riegelhuth, G. (2019). The c-its corridor project in europe has just finished testing its connected-vehicle roadworks warning system. this is the report of the findings from the experts involved in germany. In Annual Showcase (pp. 50–56).
Harrer, M., Lotz-Keens, C., Molin, H., Beek, F.O.D., Riegelhuth, G., Sauer, K., & Verweij, F. (2015). Deployment of cooperative systems on the c-its corridor in europe. In Association québécoise des transports
Helfert, M., & Dirnwöber, M. (2014). Validation of cooperative services in the fot testfeld telematik–approach and lessons learned. In Transport Research Arena (TRA) 5th Conference: Transport Solutions from Research to Deployment.
telematik, T. (2020). ECo-AT (accessed November 16). http://eco-at.info/testfeld-telematik-220.html.
Chen, S., Hu, J., Shi, Y., Zhao, L., & Li, W. (2020). A vision of c-v2x: Technologies, field testing, and challenges with chinese development. IEEE Internet of Things Journal, 7(5), 3872. https://doi.org/10.1109/JIOT.2020.2974823.
Curiel-Ramirez, L. A., Izquierdo-Reyes, J., Bustamante-Bello, M. R., Ramirez-Mendoza, R. A.,&Garcia-Barba, A. (2019). A simulation approach of the internet of intelligent vehicles for closed routes in urban environments. In 42nd International Conference on Telecommunications and Signal Processing (TSP) (pp. 672–680).
Bylykbashi, K., Qafzezi, E., Ikeda, M., Matsuo, K., & Barolli, L. (2020). Fuzzy-based driver monitoring system (fdms): Implementation of two intelligent fdmss and a testbed for safe driving in vanets. Future Generation Computer Systems, 105, 665.
Chen, C., Zhang, Y., Khosravi, M.R., Pei, Q., & Wan, S. (2020). An intelligent platooning algorithm for sustainable transportation systems in smart cities. IEEE Sensors Journal, 1–1
Adam, M. S., Anisi, M. H., & Ali, I. (2020). Object tracking sensor networks in smart cities: Taxonomy, architecture, applications, research challenges and future directions. Future Generation Computer Systems, 107, 909.
Palmieri, F., Ficco, M., Pardi, S., & Castiglione, A. (2016). A cloud-based architecture for emergency management and first responders localization in smart city environments. Computers & Electrical Engineering, 56, 810.
Yelure, B., & Sonavane, S. (2020). Performance of routing protocols using mobility models in vanet. In P. Deshpande, A. Abraham, B. Iyer, & K. Ma (Eds.), Next Generation Information Processing System (pp. 272–280). Springer Singapore: Singapore.
Harri, J., Filali, F., & Bonnet, C. (2009). Mobility models for vehicular ad hoc networks: A survey and taxonomy. IEEE Communications Surveys Tutorials, 11(4), 19.
Medeiros, D. S. V., Hernandez, D. A. B., Campista, M. E. M., et al. (2019). Impact of relative speed on node vicinity dynamics in vanets. Wireless Networks, 25(4), 1895.
Goyal, A. K., Agarwal, G., & Tripathi, A. K. (2019). Network architectures, challenges, security attacks, research domains and research methodologies in vanet: A survey. International Journal of Computer Network and Information Security, 10(10), 37.
Ramakrishnan, B., Nishanth, R. B., Joe, M. M., & Selvi, M. (2017). Cluster based emergency message broadcasting technique for vehicular ad hoc network. Wireless Networks, 23(1), 233.
Balakumar, C., & Karthikeyan, E. (2019). A review analysis on emergency data dissemination techniques in vehicular adhoc networks. Int. Journal of Scientific & Technology Research, 8, 1209.
Dar, K., Bakhouya, M., Gaber, J., & Wack, M. (2010). Evaluating information dissemination approaches in VANETs. In Proceeding 7th ACM International Conference on Pervasive Services (ICPS 2010) (pp. 120–125).
Suthaputchakun, C., Sun, Z., & Dianati, M. (2015) Impact of propagation environments on emergency message dissemination in vanets. In 7th International Conference on Ubiquitous and Future Networks (pp. 361–366).
Andrade, E., Veloso, K., Vasconcelos, N., Santos, A., & Matos, F. (2020). Cooperative monitoring and dissemination of urban events supported by dynamic clustering of vehicles, Pervasive and Mobile Computing p. 101244.
Rashid, S. A., Audah, L., Hamdi, M. M., Abood, M. S., & Alani, S. (2020). Reliable and efficient data dissemination schemein VANET: A review. International Journal of Electrical and Computer Engineering (IJECE), 10(6), 6423.
Benkerdagh, S., & Duvallet, C. (2019). Cluster-based emergency message dissemination strategy for vanet using v2v communication. International Journal of Communication Systems, 32(5), e3897.
Siddiqua, A., Shah, M. A., Khattak, H. A., Din, I. U., & Guizani, M. (2019). icafe: Intelligent congestion avoidance and fast emergency services. Future Generation Computer Systems, 99, 365.
Derder, A., Moussaoui, S., Doukha, Z., & Boualouache, A. (2019). An online target tracking protocol for vehicular ad hoc networks. Peer-to-Peer Networking and Applications, 12, 969.
Senapati, B. R., Khilar, P. M., & Swain, R. R. (2020). Fire controlling under uncertainty in urban region using smart vehicular ad hoc network. Wireless Personal Communications
Marques, M., Senna, C., & Sargento, S. (2020). Evaluation of strategies for emergency message dissemination in vanets. In 2020 IEEE Symposium on Computers and Communications (ISCC) (pp. 1–6).
Noguchi, T., Ting, Y.C., Yoshida, M., & Ramonet, A.G. (2020). Real-time cooperative vehicle tracking in vanets. In 2020 29th International Conference on Computer Communications and Networks (ICCCN) (pp. 1–6).
Tal, I., Kelly, P., & Muntean, G. M. (2016) A novel direction-based clustering algorithm for vanets. In 23rd International Conference on Telecommunications (ICT), 2016 (1–5).
Ganeshkumar, N., & Kumar, S. (2021). Obu (on-board unit) wireless devices in vanet(s) for effective communication—A review. In V. Singh, V. K. Asari, S. Kumar, & R. B. Patel (Eds.), Computational Methods and Data Engineering (pp. 191–202). Springer Singapore: Singapore.
Szigeti, T., et al. (2013). End-to-end Qos Network Design: Quality of Service for Rich-Media & Cloud Networks. Indianapolis, IN: Cisco Press.
This work was partially supported by the Coordination for the Improvement of Higher Education Personnel (CAPES) and grant 309238/2017-0 of the National Council for Scientific and Technological Development (CNPq).
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Andrade, E., Santos, A., Maciel, P.D. et al. Analyzing cooperative monitoring and dissemination of critical mobile events by VANETs. Wireless Netw (2021). https://doi.org/10.1007/s11276-021-02551-z
- Mobile crowdsensing
- Critical mobile events
- Mobility impact analysis