Research And Improvement Of Broadcast Protocol Combined Numbers Of Neighbor Nodes With Distance In Vehicular Ad-hoc Networks

Vehicular ad hoc networks (Vehicular Ad-hoc Networks, VANETs) is a self-organizednetwork formed through mutual communication between vehicles or the road units, which is animportant branch of a mobile ad hoc network (Mobile Ad-hoc Networks, MANETs). It is widelyused in the hazard warning, cooperative driving, real-time traffic, entertainment news and plays animportant role in other applications in Intelligent Transportation Systems (Intelligent, TransportSystem, ITS). Situations like sharing weather, traffic information and distributing ads are alwaysdepend on flooding broadcast, which not only takes up a lot of bandwidth resources, but alsoeasily causes the broadcast storm. Therefore, developing a high accurate rate, low end-to-enddelay and low consumption broadcast protocol has become a research hotspot of automobileindustry and academia.This paper focuses on the research of vehicular ad hoc networks broadcast protocol, puttingforward a kind of efficient broadcasting algorithm to ensure high accuracy rate, low delay and lowconsumption. In this protocol, considering the characteristic of high-speed road and city scenes aswell as vehicular network, we select the number of neighbor nodes and distance as the metric toforward messages. The main contents of this thesis include:(1) A method is proposed to improve the accuracy of neighbor list, using TDMA to resolvethe conflict problem, and also establish a more accurate neighbor list, which lays the foundationfor the research of our algorithm.(2) According to the metrics of forwarding vehicle, we propose an efficient broadcastprotocol by considering the characteristics of roads and need of protocol. The algorithm canimprove the accuracy rate, reduce the broadcast time and consumption.(3) Using the OPNET simulator for simulation. Before the simulation, we need to determinethe network model and communication model, and the specific simulation environment. In the end,comparisons are made to analyze the performance of the algorithm in all aspects.