Research On Key Techniques For Information Service Strategy And Network Resource Optimization In Large-scale Heterogeneous Vehicular Networks

In recent years,with the continuous expansion of city scale,the growing traffic volume imposes great pressures on the urban road transport system.With the development of wireless communication and intelligent driving,a new generation of intelligent transportation system is expected to greatly ease the road traffic problems of metropolis in terms of safety,efficiency and sustainable development.The efficient information service technology of vehicular network is the core of all kinds of intelligent transportation systems.However,the nature of wireless communication and the mobility of vehicles bring great challenges on the information service in vehicular networks.First,all the data has to be received before the strict deadline in order to satisfy the real-time service request.Meanwhile,timely data update is required to ensure the quality of temporal data.Data dissemination and data update compete for the same bandwidth resource,resulting in the degradation of system performance.Second,in the scenario of large-scale temporal data dissemination,the completion of service request requires the collaboration of roadside unit(RSU)and mobile vehicle.However,due to the limited communication range of wireless communication,the vehicle cannot complete its service request in a single RSU.Third,vehicular networks are essentially a new type of wireless network with heterogeneous network resources and heterogeneous information.The traditional framework cannot effectively manage the network resources in heterogeneous vehicular environment.In view of the above problems,this article investigates the information service in vehicular networks systematically in view of service framework,model construction and algorithm design.The main contributions are included as follows:1)We investigate the real-time information service in vehicular networks.First,we establish the data quality model to quantitatively evaluate the timeliness of temporal data and theoretically analyze the effect of bandwidth allocation ratio on service quality and service ratio.On this basis,an adaptive-update request scheduling algorithm is designed to dynamically allocate the bandwidth resources for data update and data dissemination according to the quality of cached data and the characteristics of service request.Finally,we design the simulation platform and verify the superiority of the proposed algorithm in improving the service quality and the service ratio.2)We investigate the large-scale temporal data dissemination problem in hybrid V2I/V2 V communications.First,we propose the centralized scheduling based temporal information service framework in multi-RSU scenario,and establish the system model for service quality and delivery ratio based on the coordination of multiple RSUs and mobile vehicles.On this basis,we propose a multi-objective evolutionary algorithm to generate a set of non-dominated solutions and finally select the optimal solution according to the designed priority function,in order to meet the service requirements of different application scenarios.The experimental results verify the scalability and adaptability of the algorithm under different application scenarios.3)We study the network resources optimization problem of the heterogeneous vehicular networks.First,we propose the software-defined network(SDN)based service framework in heterogeneous vehicular networks and realize the unified management of network resources and data scheduling through the control plane.By analyzing the heterogeneity of information service and network resource,we design the coding-based data broadcasting strategy for each network infrastructure and network selection strategy for each mobile vehicle.The experimental results show that the algorithm can effectively improve the bandwidth utilization and reduce both service delay and access cost in different application scenarios.