Research On Task Offloading And Resource Allocation Strategy For Vehicle Edge Computin

With the arrival of 5G era,higher requirements are put forward for mobile network in terms of mobility,security and delay.Mobile edge computing(MEC)is a new distributed computing method based on mobile communication network.With the development of the Internet of Things,intelligent vehicle services generate high performance requirements,such as low latency response,high-speed communication and intensive computing.Therefore,vehicle edge computing(VEC)emerges as the times require and gradually becomes a new paradigm with research prospects.The introduction of VEC server greatly improves the computing capacity of the Internet of Vehicles,but also introduces a series of problems such as computing unloading and resource allocation.Considering the limited and selfish resources of the edge and the intensive computing needs of intelligent vehicles,how to motivate the edge to participate in the task unloading of intelligent vehicles,and make reasonable use of edge resources to meet the computing needs of intelligent vehicles is one of the problems that need to be solved today.In view of this,this paper first proposes a second-order Stackelberg incentive framework for edge computing,which encourages the VEC server to unload some of the intensive computing tasks generated by vehicles,reduces delays,and improves the quality of service of the Internet of Vehicles.At the same time,it is noted that there are a large number of idle vehicles in the city.Therefore,this paper considers the idle vehicles in the same area as facilitators,and further proposes a three-level incentive framework for the cooperative participation of edge and assisted vehicles.The main contents and innovations of this article are as follows:(1)Aiming at the intensive computing tasks of intelligent vehicles in the Internet of Vehicles,this paper studies the unloading strategy of vehicle edge computing based on Stackelberg theory.The interaction mode between VEC server and Computation-required Vehicle(CRV)is a Stackelberg game with single leader and multiple followers.In the first stage,VEC server,as the leader,determines the price of unit computing resources to the vehicle;In the second stage,the vehicle,as the follower,determines the resource demand strategy to the VEC server.This strategy formulation process of both sides is repeated until Nash equilibrium is reached.This paper strictly deduces and proves the existence and uniqueness of the Nash equilibrium of the Stackelberg game in the above two stages.(2)In view of the limited computing and storage resources of VEC server,this paper designs a vehicle task unloading model based on multi-party cooperation.Computationassisted vehicle(CAV)uses its idle computing resources to assist the VEC server to unload the computing tasks of other intelligent vehicles.In order to stimulate the participation of VEC server and CAV,this paper designs a comprehensive resource management and cost-benefit and pricing mechanism.This design effectively integrates and utilizes the communication mode and computing mode between participants,forming a three-stage Stackelberg game.In the first stage,CAV determines the optimal price of computing resources for VEC servers;In the second stage,the VEC server determines the optimal resource demand based on the pricing given by CAV,and determines the calculated resource price of CRV;In the third stage,CRV determines the optimal resource strategy.This paper theoretically proves the existence and uniqueness of Nash equilibrium(NE)for each Stackelberg game.When in Nash equilibrium,no participant will unilaterally violate the strategy.The simulation results show that the model is effective and robust.The rapid development of MEC technology and the popularity of smart cars provide The rapid development of MEC technology and the popularity of smart cars provide the feasibility of VEC technology.In this paper,edge computing is introduced into the Internet of Vehicles,which uses VEC servers and idle resources to unload the intensive computing tasks generated by vehicles,effectively improving the task processing capacity and quality of service of vehicles,while maximizing the benefits of each participant.Vehicle edge computing provides low latency,high bandwidth computing services for resource constrained vehicles,effectively improves the quality of service of vehicles,and shows broad application prospects in the context of the 5G communication era.Since vehicle task offloading is still in the early stage of development,the difficulties brought by the complexity of the offloading decision algorithm,the privacy of data,and the high mobility of vehicles still need to be explored and solved.