Research On QoS-driven Network Access Selection And Resource Collaborative Optimization Algorithm In Vehicular Heterogeneous Network

With the advancement of communication technology and the vigorous development in the field of intelligent transportation,many new types of services such as mobile TV,streaming media services or security applications are required to make vehicular networks provide higher quality of service when traveling by car.How to meet the different needs of users in the vehicular network environment is an urgent problem to be solved.Vehicular heterogeneous network(VHN)is a wireless vehicular network that integrates various wireless communication technologies to realize seamless access and dynamic switching between different types of networks that overlap with each other,and can effectively meet the diversity needs of users.In vehicular heterogeneous networks,the network access selection algorithm can be used to select the optimal target network node for the user.This paper focuses on the network access selection and resource cooperation optimization algorithm in vehicular heterogeneous networks,and the specific research contents are as follows:First of all,aiming at the problem of the coordination price and the quality of service being difficult to be equalized in vehicular heterogeneous networks,a multi-objective decision network access algorithm based on game theory is proposed.Based on the Shapley formula of game theory,the algorithm calculates the marginal revenue to formulate a mechanism that can promote the cooperative communication between vehicles.Based on the multi-objective selection strategy of optimization theory,the two parameters of the price and service amount of the target access network node are comprehensively considered,and the best vehicle nodes are chosen to work with them and access the roadside network unit for Internet service.The simulation results show that the different ratios of price parameters and service parameters directly affect the selection of target cooperative vehicles.In addition,the proposed algorithm can achieve higher quality of service while accessing the network at a lower price compared with the existing access mechanisms based on pricing in the terms of access cost and the information transmission rate.Secondly,aiming at the problem of the high adaptation complexity of collaborative nodes in vehicles caused by high vehicle node mobility in vehicular heterogeneous network and the frequent changes of network topology,a graph-based collaborative optimization algorithm for vehicular heterogeneous network resources is proposed.The proposed algorithm introduces the concept of service amount instead of instantaneous transmission rate as a index of link status,fully considers the constraints of transmission delay in network,and models the node selection and resource adaptation of vehicular network based on the bipartite graph and use KM(Kuhn-Munkres)algorithm to achieve the maximum weighted matching in the bipartite graph.Experimental results show that compared with the resource cooperation algorithm based on instantaneous transmission rate,the proposed algorithm can describe the link quality in vehicular network more accurately and realize the optimal resource allocation among cooperative vehicles in the vehicular heterogeneous network environment.Under the different vehicle speed and vehicle density,the proposed algorithm can improve the data throughput of the vehicular network.