Abstract
With the worldwide growth in vehicles due to the increase in population, Vehicular ad hoc networks (VANETs) have attracted researchers both from academia as well as the industry. It provides a smart and efficient driving experience for drivers. Traditional VANET suffers from various issues of security, QoS, and latency. To address these problems, software-defined network (SDN) based VANET is one of the key components in the field of transportation systems. It plays an important role in VANET and also provides features such as flexibility and programmability. It also deals with security, dynamism and heterogeneous features of the VANET environment. It helps the VANET in scalability and dynamic deciding the optimal path and aids the routing in situations of a congestion in VANET. In this paper, we have explored the suitability of SDN in VANET. We have also compared the various state-of-the-art approaches existing. These approaches are based on the concepts of clustering, geo broadcast, road side unit (RSU) based Geocast, fog and SDN based VANET, cloud-based VANET. It is evident from the literature that SDN based VANET provides better QoS, latency, and also efficiently handles heterogeneity. It also has good efficiency in comparison to a traditional network. Security is a crucial parameter in the SDN and hence has been explored in the paper. We have further highlight the open issues and challenges encountered while merging the VANET with SDN. This paper give insights to the researchers willing to start work in this domain.
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Trivedi, H., Tanwar, S., Thakkar, P. (2019). Software Defined Network-Based Vehicular Adhoc Networks for Intelligent Transportation System: Recent Advances and Future Challenges. In: Singh, P., Paprzycki, M., Bhargava, B., Chhabra, J., Kaushal, N., Kumar, Y. (eds) Futuristic Trends in Network and Communication Technologies. FTNCT 2018. Communications in Computer and Information Science, vol 958. Springer, Singapore. https://doi.org/10.1007/978-981-13-3804-5_24
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DOI: https://doi.org/10.1007/978-981-13-3804-5_24
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