Research On Multi-access Edge Computing And Cache Technology In D2D-based Internet Of Vehicles

With the popularization of Internet of Vehicles(Io V),the number of vehicles and the amount of data generated by vehicles are increasing.SU to the upper limit of the vehicle's own computing resources and battery capacity,performing tasks locally on the vehicle cannot meet the requirements of low latency and low energy consumption.Multi-access Edge Computing(MEC)technology provides cloud computing and storage capabilities at the edge of a multiaccess network.MEC technology offloads the tasks of the vehicle to the MEC server for execution based on task offloading.This reduces the delay and energy consumption of vehicles to perform tasks.However,the computing and storage resources of the MEC server are limited,which leads to increased delay and energy consumption when the number of vehicles and the amount of data generated by vehicles is large.Device-to-device(D2D)task offloading technology can use idle computing resources of neighboring vehicles to process task requests and further reduces the delay and energy consumption of vehicles to perform tasks.Task caching technology avoids the delay and energy consumption of uploading repeated tasks by caching highly popular request tasks on the MEC server.However,how to properly allocate channel resources between cellular and D2 D communication links to ensure D2 D communication reliability while minimizing the delay and energy consumption of all Cellular User Equipment(RU)that communicate with the base station and jointly optimize MEC task offloading and task caching in D2D-based Io V have become critical issues that need to be resolved.This article studies the above problems and the work results are as follows:1.Aiming at the problem of channel resource allocation and D2 D communication reliability of Io V system,this paper proposes a MEC task offloading method in D2D-based Io V.The task offloading strategy,transmission power,and channel resource allocation model are modeled as a mixed integer non-linear programming problem,and the optimization problem is maximizing the sum of the benefits of the delay and energy consumption of all RU.This paper proposes a heuristic algorithm that decomposes the optimization problem into several suboptimization problems to solve.Simulation results show that this solution ensures the reliability of D2 D communication while minimizing the delay and energy consumption of RU.2.Aiming at the problem of insufficient computing resources of the MEC server,this paper proposes a MEC task offloading and task caching joint optimization method in D2D-based Io V.The vehicle can choose three task offloading strategy: local execution,MEC offloading,and D2 D offloading.At the same time,the cache service is deployed on the MEC server.The task offloading strategy and task caching strategy are modeled as a integer non-linear programming problem,and the optimization problem is minimizing the weight sum of delay and energy consumption of all vehicles.This paper proposes a heuristic algorithm that solves the task offloading strategy first and then solves the task caching strategy.Simulation results show that compared with the scheme that does not consider D2 D offloading and task caching and the local execution scheme,this solution has lower delay and energy consumption.