Research On Data Dissemination Scheme For Urban Vehicular Ad-Hoc Network

Vehicular ad-hoc network (VANET) has become a new research focus in wireless network and intelligent traffic fields. Comparison to existing wireless ad-hoc networks, Vehicular ad-hoc network has many new characteristics, such as tubular network space, high movement speed, poor link stability, etc. The dissemination scheme of existing ad-hoc network can’t be applied directly in such network. The research on the new data dissemination is necessary and has important theoretical and practical value.The paper firstly carries out an analysis of vehicular ad-hoc network characteristics which is based on the real vehicular trace. We collect the vehicular trace captured from real traffic environment. Then we use the map matching and topological interpolation to solve the problem of large time granularity and poor data accuracy. We analyze the network connectivity, link characteristics, network centrality of vehicular ad-hoc network under real traffic environment. We establish the simulation platform to compare and analyze a variety of existing mobility models and give the evaluation of reality for these models.Because nodes space distribution is non-uniform in real traffic environment. It causes great differences of network connectivity in different regions of the network. Therefore the redundancy of data dissemination should be adjusted dynamically according to the current density of nodes to avoid the degradation of performance or waste of network resource. The paper uses the random graph as theory foundation, proposed data dissemination scheme based on limited flooding mechanism. We set a dynamic up-bound on hop of packets according to the nodes density of current region in the process of data dissemination. The numbers of redundant packet copies are effectively reduced in regions with strong connectivity. The trade-off and the balance are obtained between the performance of data dissemination and consumption of network resources.Based on the principle of "hot-spot" regional priority cover, we firstly extract the "hot-spot" regions using real vehicular traces. Then we use RSU to compose the "backbone network" and use the maximum span-tree algorithm to calculate the number and position of RSU. This method not only can get better effect of connectivity enhancement, but also that can reduce the cost of RSU deployment.