Recently, Vehicular Ad-hoc Network (VANET) has been one of the emerging fields of research. Many researchers are doing their research on various challenges of VANET. Congestion or blockage has become a critical issue in intelligent transportation systems, and this problem may arise daily due to the usage of smart technology in VANET. So we need some mechanism which controlscongestion. This paper present the trustworthy, long-lasting and consistent block chain congestion control mechanism using the heterogeneity of Dullening Nural Network (DNN), Q-Learning, and Software Define Network (SDN) model for an accurate result, fixed infrastructure, together with a correct prediction of congestion when it occurs at the edge of the network and give the fast and correct decision of congestion w.r.t VANET trust, Quality of service (QOS) and other vehicles current request. The focus of our research is on distributed SDN Technology and block chain technology for the development of smart cities and linked vehicles. So we proposed an inexpensive mechanism with low latency and a low bandwidth block chain system. Based on the Simulation result, our proposed architecture gives 82% and 98% reliability and efficiency gain in a congestion environment compared to traditional approaches. This paper aims to increase throughput, Packet Delivery Ratio (PDR), energy consumption time, and less end-to-end delay and routing overhead during communication.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.