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Data Transmission Using IoT in Vehicular Ad-Hoc Networks in Smart City Congestion

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Abstract

Development of Internet of Things (IoT) enables smart city advancement throughout the world. Increasing number of vehicles has brought focus on road safety precautions and in-vehicle communication. This is the right time to focus on the development of new applications and services for vehicular environments. The Vehicular Ad-hoc Networks (VANETs) are an interesting range of Mobile Ad-hoc Networks (MANETs) where the Vehicle to Vehicle (V2V) and vehicle roadways transmission is possible. The V2V scheme is fresh by combining Wireless Fidelity (Wi-Fi), Bluetooth and other all sorts of communication standards. An immense number of nodes working with these networks and due to their immense displacements, the analysis is prevailing regarding the possibility of routing standards. The estimation of conventional routing standards for MANETs illustrates that their behaviors are minimal in VANETs. The intention is to make use of mediators for routing with an effort to address the before described issues. The mediators are accountable for gathering data related to routing and identifying the optimal paths for forwarding information packets. The routing scheme is based on group routing standards and data cluster framework for locating the best possible routes. In this paper, we analyze smart cities vehicle communication development by implementing IoT. We also discuss the ways to minimize the limitations connected to IoT deployment and implementation in smart city environment using multi mediator scheme.

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References

  1. Talreja R, Sathish S, Nenwani K, Saxena K (2016) Trust and behavior based system to prevent collision in IoT enabled VANET," 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), Paralakhemundi, pp. 1588–1591. https://doi.org/10.1109/SCOPES.2016.7955707

  2. Hasson ST, Hasan ZY (2017) Roads clustering approach’s in VANET models. 2017 annual conference on new trends in information & communications technology applications (NTICT), Baghdad, pp. 316–321. doi: https://doi.org/10.1109/NTICT.2017.7976140

  3. Lazar SA, Stefan CE Future Vehicular networks: What control technologies? vol 2016. 2016 International Conference on Communications (COMM), Bucharest, pp 337–340. https://doi.org/10.1109/ICComm.2016.7528203

  4. Chatrapathi C, Rajkumar MN, Venkatesakumar V (2015) VANET based integrated framework for smart accident management system. 2015 International Conference on Soft-Computing and Networks Security (ICSNS), Coimbatore, pp 1–7. https://doi.org/10.1109/ICSNS.2015.7292411

    Book  Google Scholar 

  5. Anandakumar H, Umamaheswari K (2017) Supervised machine learning techniques in cognitive radio networks during cooperative spectrum handovers. Clust Comput 20(2):1505–1515

    Article  Google Scholar 

  6. Ayyappan B, Kumar PM (2016) Vehicular Ad Hoc Networks (VANET): Architectures, methodologies and design issues. 2016 Second International Conference on Science Technology Engineering and Management (ICONSTEM), Chennai, pp 177–180. https://doi.org/10.1109/ICONSTEM.2016.7560946

    Book  Google Scholar 

  7. Talreja R, Sathish S, Nenwani K, Saxena K (2016) Trust and behavior based system to prevent collision in IoT enabled VANET. 2016 International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES), Paralakhemundi, pp 1588–1591. https://doi.org/10.1109/SCOPES.2016.7955707

    Book  Google Scholar 

  8. Abdelgadir M, Saeed R, Babiker A (2016) Vehicular Ad-hoc Networks (VANETs) dynamic performance estimation routing model for city scenarios. 2016 International Conference on Information Science and Communications Technologies (ICISCT), Tashkent, pp 1–8. https://doi.org/10.1109/ICISCT.2016.7777397

    Book  Google Scholar 

  9. Xie S, Hu X, Xin Z, Li L Time-Efficient Stochastic Model Predictive Energy Management for a Plug-In Hybrid Electric Bus with Adaptive Reference State-of-Charge Advisory. IEEE Trans Veh Technol PP(99):1. https://doi.org/10.1109/TVT.2018.2798662

  10. Anandakumar H, Umamaheswari K (2017) An Efficient Optimized Handover in Cognitive Radio Networks using Cooperative Spectrum sensing. Intelligent Automation & Soft Computing:1–8. https://doi.org/10.1080/10798587.2017.1364931

  11. Khayamy M, Chaoui H (2018) Efficient PMSM Inverter-Based Drive for Vehicular Transportation Systems. IEEE Trans Veh Technol PP(99):1. https://doi.org/10.1109/TVT.2018.2798359

    Article  Google Scholar 

  12. Ucar S, Ergen SC, Ozkasap O (2016) Multihop-Cluster-Based IEEE 802.11p and LTE Hybrid Architecture for VANET Safety Message Dissemination. IEEE Trans Veh Technol 65(4):2621–2636. https://doi.org/10.1109/TVT.2015.2421277

    Article  Google Scholar 

  13. Ji J, Khajepour A, Melek WW, Huang Y (2017) Path Planning and Tracking for Vehicle Collision Avoidance Based on Model Predictive Control With Multiconstraints. IEEE Trans Veh Technol 66(2):952–964. https://doi.org/10.1109/TVT.2016.2555853

    Article  Google Scholar 

  14. Liang L, Peng H, Li GY, Shen X (2017) Vehicular Communications: A Physical Layer Perspective. IEEE Trans Veh Technol 66(12):10647–10659. https://doi.org/10.1109/TVT.2017.2750903

    Article  Google Scholar 

  15. Arulmurugan R, Sabarmathi KR, Anandakumar H (2017) Classification of sentence level sentiment analysis using cloud machine learning techniques. Clust Comput. https://doi.org/10.1007/s10586-017-1200-1

  16. Zhu L, He Y, Yu FR, Ning B, Tang T, Zhao N (2017) Communication-Based Train Control System Performance Optimization Using Deep Reinforcement Learning. IEEE Trans Veh Technol 66(12):10705–10717. https://doi.org/10.1109/TVT.2017.2724060

    Article  Google Scholar 

  17. Wang C, Yu FR, Liang C, Chen Q, Tang L (2017) Joint Computation Offloading and Interference Management in Wireless Cellular Networks with Mobile Edge Computing. IEEE Trans Veh Technol 66(8):7432–7445. https://doi.org/10.1109/TVT.2017.2672701

    Article  Google Scholar 

  18. Anandakumar H, Umamaheswari K (2017) A bio-inspired swarm intelligence technique for social aware cognitive radio handovers. Comput Electr Eng. https://doi.org/10.1016/j.compeleceng.2017.09.016

  19. Cui J, Zhang J, Zhong H, Xu Y (2017) SPACF: A Secure Privacy-Preserving Authentication Scheme for VANET With Cuckoo Filter. IEEE Trans Veh Technol 66(11):10283–10295. https://doi.org/10.1109/TVT.2017.2718101

    Article  Google Scholar 

  20. Hou X, Li Y, Chen M, Wu D, Jin D, Chen S (2016) Vehicular Fog Computing: A Viewpoint of Vehicles as the Infrastructures. IEEE Trans Veh Technol 65(6):3860–3873. https://doi.org/10.1109/TVT.2016.2532863

    Article  Google Scholar 

  21. Zhang C, Huang Y, Jing Y, Yang L (2017) Energy Efficient Beamforming for Massive MIMO Public Channel. IEEE Trans Veh Technol 66(11):10595–10600. https://doi.org/10.1109/TVT.2017.2756994

    Article  Google Scholar 

  22. Sharif A, Li JP, Sharif MI (2018) Internet of Things network cognition and traffic management system. Cluster Computing 1–9

  23. Ying B, Nayak A (2017) Anonymous and Lightweight Authentication for Secure Vehicular Networks. IEEE Trans Veh Technol 66(12):10626–10636. https://doi.org/10.1109/TVT.2017.2744182

    Article  Google Scholar 

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Correspondence to Muhammad Asim Saleem or Zhou Shijie.

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Saleem, M.A., Shijie, Z. & Sharif, A. Data Transmission Using IoT in Vehicular Ad-Hoc Networks in Smart City Congestion. Mobile Netw Appl 24, 248–258 (2019). https://doi.org/10.1007/s11036-018-1205-x

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