Abstract
In vehicular ad-hoc inetwork (VANET), the dissemination of traffic information and road conditions from source vehicle to many destination vehicles on the road plays an important role in VANET. The multiple messages are needed to provide the requirement of safety and non-safety applications. This paper investigates the congestion problem due to the control overhead messages and proposes an optimal adaptive data dissemination protocol (OAddP). The proposed protocol (OAddP) utilizes the optimal clustering and control overhead reduction algorithms to maximize the data dissemination efficiency and Success rate with different traffic flows. The Whale optimization Algorithm (WOA) is used for clustering and cluster head (CH) selection. Then, a predictor-based decision making (PDM) algorithm is used to minimize the control overhead messages in network. The proposed algorithm is simulated & compared with adaptive data dissemination protocol (AddP) for varying traffic flow & vehicle density. The simulation results show better performance in terms of higher success rate and data dissemination efficiency.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
