The Research On Joint Optimization Method Of Quality Of Service And Security In Vehicular Networks Based On Game Theory

With the deployment of 5G technology around the world and the ever-increasing number of vehicles,vehicular networks(VNs)have been regarded as an important part of intelligent transportation systems(ITS).The salient characteristics of VNs such as high dynamic,uncertainty,open channels,and limited network resources lead to the stringent requirements of vehicles on communication quality and security.However,with the explosive increase of vehicles and the emergence of various applications,satisfying the huge and heterogeneous requirements of communication quality and security for different vehicles could be challenged by the limited resources of vehicles and VNs,the limited information on the characteristics or behaviors of the other nodes,the independently operated and protocol layers of VNs,and the complex interactions among heterogeneous nodes.Game theory has shown its potential to deal with the above challenges by providing a powerful mathematical tool to analyze and model the complex interactions among different decision-makers in resource-constraint VNs.It enables decisionmakers to adopt optimal strategies to obtain the satisfctoryuality of service and security.This study employs the advantage of the game to construct efficient and secure decision-making approaches to satisfy the stringent requirements of vehicular nodes on communication quality and security.The main contributions are listed as follows:1)To deal with the possible conflicts between communication quality and security caused by the limited resources of vehicles,this study proposes a game-theoretical approach for vehicleto-vehicle(V2V)communication based on Merkle authentication.A complete information game model is constructed to balance the communication quality and security based on Merkle authentication,and the optimal construction strategy of the Merkle tree is obtained.Simulation results demonstrate that the proposed method enables the vehicle to adaptively adjust the strategy according to the environment to obtain the satisfied communication quality and security.2)To overcome the difficulty of obtaining complete information on the other nodes(especially malicious nodes)in the dynamic and uncertain VNs,a Bayesian game theoretical approach is proposed to jointly optimize the V2 V communication quality and security in the uncertain environment.By employing the advantage of the Bayesian game in modeling the decision-making for the incomplete-information cases,this study constructs three Bayesian game models based on three types of distributions,and the optimal strategies and distribution parameters for these games are obtained.By comparing with the complete information game,the three types of optimal parameters of the Bayesian games are demonstrated to be precise.This approach enables vehicles to adaptively adjust the transmission and authentication strategies according to the amount of information acquired to obtain satisfactory communication and security performance.3)Considering the influences of the physical layer and MAC(Medium Access Control)on the communication performance,a cross-layer tradeoff for vehicular communication quality and security is proposed based on the game theory.A two-stage game-theoretic model is constructed to deal with the external decision-making of competitive vehicles and the internal decisionmaking of an individual vehicle node,respectively.The optimal external strategy is proved and calculated for the first stage,which is used as an input of the internal game.According to the optimal transmission power of the external game,a game model is constructed to make a tradeoff between the communication quality and security of the internal game.Besides,the optimal resource allocation strategy is obtained for the internal game.Simulation results demonstrate that the vehicle node can dynamically adapt the optimal strategy to the environment,and efficient and secure communication performance can be obtained.4)To overcome the resource limitation in the emerging vehicular edge computing(VEC)networks and the heterogeneity between the VEC server and the vehicle,an efficient and secure game theoretical approach is proposed for resource allocation and task offloading in VEC networks.A cooperative resource allocation and task offloading approach is constructed by applying the price incentive mechanism and the matching game theory.VEC servers and vehicles can cooperatively negotiate the optimal resource allocation and pricing strategies.Besides,vehicles can competitively decide the optimal offloading strategies.This approach is proved to be optimal and stable.Simulation results demonstrate that the proposed approach achieves superior system performance and higher efficiency,especially when the system workload is heavy.