A Game Theoretic Approach To Research On Pricing And Caching Strategies For Vehicular Networks

The Internet of Vehicles is a huge information exchange network that enables vehicles,roadside facilities,and pedestrians to communicate with each other.The Roadside Units(RSU)make profit from providing content service for vehicles using V2R(Vehicle to Roadside Unit)communication which can meet the entertainment needs of most vehicle users.Facing the severe market competition and massive content files,how RSUs develop the optimal content pricing and caching strategies and raise their own revenue is the main research content of this thesis.The details are as follows:(1)Content pricing problem of RSUs.In the research of pricing strategy,the location distribution of RSUs operated by two different operators is modeled as a onedimensional homogeneous Poisson point process with different densities firstly,and the average achievable rate between RSUs and vehicles is derived using stochastic geometry theory.Then the utility functions of the two operators and the vehicle are designed based on the average achievable rate of unit bandwidth,and the interaction among them is modeled as a Stackelberg game.Finally,the optimal pricing strategy of the operators is obtained by solving the game equilibrium point.Simulation results show that the game model proposed in this thesis can maximize the utility of both operators and the vehicle at the same time.(2)Content caching problem of RSUs.In the research of caching strategy,firstly,the location distribution of the base stations and RSUs is modeled as a two-dimensional and one-dimensional homogeneous Poisson point process respectively.The coverage probability for effective service of the heterogeneous network composed of the base stations and RSUs is derived and the selection probability of vehicles between base stations and RSUs is calculated.The revenue functions of the base stations and RSUs is designed based on the coverage probability for effective service and the selection probability of vehicles,and the interaction between them is modeled as a Stackelberg game.Then the optimal caching strategy of RSUs is obtained by solving the game equilibrium point,and the operation status adjustment scheme for RSUs is designed finally.Simulation results show that the caching incentive mechanism for RSUs based on Stackelberg game can effectively increase the revenue of both the base stations and RSUs.The thesis innovatively proposes a pricing strategy game model and a caching incentive mechanism for RSUs based on Stackelberg game.Pricing and Caching problems of RSUs in the Internet of Vehicles are solved using stochastic geometry theory and game theory,which provides a reference for future research on the deployment of RSUs as well as the pricing and caching strategies in the Internet of Vehicles.It is an effective design example of game theory applied to the Internet of Vehicles scenario.