| Vehicular Ad-hoc Network (VANET) is composed of the vehicles with OBU and the RSUs installed in the roadside. RSUs is an information transfer hub of vehicles in the VANET and the Internet. In the initial stages of the deployment of RSUs in VANET, the number of RSU which can be deployment in the target region is restricted. But, the number of vehicles and the increasing demand of information in the VANET are far more than the carrying capability of the RSUs. Therefore, to satisfy the communication demand of the vehicles and maximize the deployment benefit in the VANET, we should optimize the location of each RSU within the limitation of RSU’s deployment number.Regarding the vehicle within range of a wireless communication as gain efficiency, the profit of vehicles which be overlaid possess highly indeterminate and spatiotemporal dynamic, due to the dynamic nature and spatiotemporal differences of the vehicles node in VANET. Therefore, in practice, we usually determine the coverage benefit of the RSUs in road network. We confirm the weight of each road by synthesizes vehicle density, region-character and number of the roads in the VANET, and considering the weighted sum of weight value of all sections which under the cover of RSUs as RSUs deployment benefit. Let P denote all kinds of the RSU deployment scheme, and each RSU deployment scheme in P is constructed by a sense of feasible positions of the RSUs. Hence, searching for the positions of RSUs with best deployment benefit is referred to as the Research of RSU Deployment Algorithms for VANET.In this thesis, we propose a RSU deployment problem model (RDPM) for the placement of RSUs, and introduce an optimal deployment scheme of RSUs on a highway-like roadway and an urban region based on the model. The main contributions of the thesis are as follows:Firstly, we introduce a RSU deployment problem model. The RSUs deployment problem model is consisted of a road-network model which can describe the curve road and a benefit model to compute the deployment benefits.Secondly, an optimal RSU deployment strategy is proposed to address the RDPM in highway-like roadway scenarios. We considering four deployment scenarios to analysis the optimal deployment strategy in highway-like roadway. Afterwards we simulate each case of RSU deployment scenario, and compared the simulation results with random deployment strategy. Simulation results show that our proposed approach can achieve optimal deployment efficiency.Finally, we introduced an optimal RSU deployment strategy to resolve the RDPM in an urban region. First, we transform the RSU deployment problem into an optimization problem, and then we considering the genetic algorithm and particle swarm optimization algorithm as an optimization solution to RDPM. Afterwards, we implementing each algorithm to deal with RDPM by MATLAB, and compared the simulation results with BEH deployment strategy. Simulation results show that our proposed approach achieves optimal solutions with much higher deployment interests. |
