Research On The Vehicular Edge Computing Fair Access Mechanism Based On Age Of Information

With the rapid development of automotive telematics technology,modern vehicles can be interconnected through Internet of Vehicles(Io V)technology and exchange massive amounts of information with the surrounding environment.Vehicles collect massive amounts of data through smart sensors and high-definition cameras,and process the data to provide onvehicle application services.However,the computing and storage capabilities of a vehicle is limited,and it is impossible to process such a large amount of data efficiently and timely.Vehicular Edge Compute(VEC)can effectively assist vehicles to perform task processing.In on the vehicular edge computing,vehicles generally use the IEEE 802.11 protocol to access the channel and offload tasks to the edge server,and use its rich computing resources to assist itself computing needs and provide useful information to vehicles,thereby effectively solving road safety problems,alleviating traffic congestion and improving driving comfort.Age of Information(Ao I)is an emerging performance metric that can be used to measure the freshness of information.In the Vehicular Edge Computing,vehicles are extremely sensitive to the freshness of information,and outdated information will lead to traffic accidents because vehicles cannot receive useful information in time.The Vehicular Edge Computing environment is complex,with the characteristics of high-velocity vehicle movement,frequent changes in network topology,and uncertain access parameters,which make the age of information of vehicles change in real time during the access process.This further results in the unfairness of age of information and the amount of data transmitted by different vehicles during the access process.The above unfair access phenomenon will cause vehicles to fail to receive useful information timely,and road safety cannot be guaranteed.Therefore,it is very important to study the access mechanism of the Vehicular Edge Computing based on age of information to ensure access fairness.This paper focuses on novel communication metric-age of information,and studies the fair access mechanism of on the vehicular edge computing based on age of information.The main research works included in this paper are as follows.(1)Aiming at the problem that it is difficult to solve the problem of vehicle information age in real-time observation scenarios,the research on the benefits of age fairness is carried out by discretizing the age of transmitted data information.This section considers the discretization of information age,and analyzes the age fairness when different minimum competition window combinations are used.The continuous age process is discretized,and the calculation method of the average Ao I in a discrete time observation interval is deduced.Then use the average Ao I of all communication devices in the network to define the fairness loss of the network,and derive the age fairness utility of the network.Finally,based on the real-time IEEE 802.11 protocol,the age fairness utility of the network is simulated when the communication devices in the network use different Minimum Contention Window(MCW)combinations,and a qualitative analysis is given.(2)The MCW and the number of vehicles in the Io V are usually time-varying,which will allow vehicles to obtain different network access opportunities,resulting in a substantial increase in the average Ao I of data transmitted by different vehicles.Aiming at the above problems,an adaptive Vehicle-to-Infrastructure(V2I)access scheme is proposed to ensure age fairness of vehicle information in the Internet of Vehicles.This part of the work considers the adaptive adjustment of the MCW of the vehicle in the time-varying scenario,and obtains the optimal MCW adaptive adjustment strategy through learning.First,an intelligent vehicle node is designed by defining the state space,action space and reward mechanism of the system to ensure the age fairness of the data transmitted by different vehicles in the network.Then,through the improved Deep Q-Network(DQN)algorithm to learn and predict the optimal window value for each discrete-time observation interval.Finally,it is verified by simulation that the proposed adaptive access scheme can achieve the highest network age fairness benefit next to the ideal optimal.(3)Considering the highway platoon scenario,the task offloading performance of highway platoon based on IEEE 802.11 Distributed Coordination Function(DCF)is analyzed.The fairness of the data transmitted by vehicles is a key factor for the safe driving of platoons.Due to the different driving velocities of vehicles in different lanes,the amount of data transmitted by vehicles during the existence of the base station(BS)coverage is different,which affects the driving safety of the platoon.Ao I is used to measure the freshness of the data.The larger average Ao I of the vehicle means that the data transmitted by the vehicle is not received by the receiver in time.This section considers autonomous driving platoon scenarios while optimizing communication fairness and network average Ao I.The fairness index of vehicle transmission data in the network is derived.Then based on Stochastic Hybrid System(SHS),the closed-form expression of the average Ao I of the network is derived,and the average number of vehicles in the network is derived.Finally,a heuristic algorithm is used to construct a multi-objective equation to solve the optimal network access parameters of the vehicle,and the obtained optimal solution is verified by simulation to achieve the fairness of the vehicle transmission data and the relatively small average Ao I of the network.