Resource Allocation In Edge Computing For Assisted Driving

Internet of Vehicles is one of the key technologies to realize intelligent transportation in the future.It forms an ecological chain of vehicle operation management through V2 X communication technology combined with edge cloud architecture.The assisted driving technology realized by Augmented Vehicular Reality(AVR)can display the current traffic situation in real time,assist drivers to make reasonable driving decisions in time and ensure driving safety.Due to the extremely demanding delay and computation requirements of AVR,and the computing ability of vehicle itself is limited in high-density urban intersection environment.Integrating Internet of Vehicles with multi-access edge computing technology is an effective solution to this kind of delay-sensitive and computing-intensive application problem.Based on the above problems,this paper proposes a Task offloading and Resource allocation with maximum Throughput(ToRaT)algorithm for the urban intersection communication scenario,which can achieve the goal of maximizing system throughput on the premise of ensuring the completion of tasks.Firstly,the problem model is established,including the communication model of the vehicle,the task model with three characteristics of data volume,computation volume and time delay,and the computation model.The total delay of local computing,V2 V offloading and V2 I offloading in the computation model is analyzed in detail.Then,according to the problem model,the optimization goal of the system throughput maximization and its constraints are summarized.Since the original problem is proved to be NP-hard and it is difficult to get the optimal solution,this paper proposes a step-by-step solution.Firstly,the minimum rate limit within the tolerable delay of the task is calculated.On this basis,the optimal power allocation is obtained according to the convex optimization theory,and the throughput gains under V2 V offloading and V2 I offloading are compared respectively.Task offloading decisions are given based on the gain size.Then the maximum matching algorithm of bipartite graph is used to solve the channel assignment problem,and the minimum computational resource allocation satisfying the task tolerant delay is obtained according to the decision of offloading and the result of wireless resource allocation.Finally,through simulation experiments,the system throughput of ToRaT algorithm,V2 V first algorithm and V2 I first algorithm under the factors of task number,vehicle speed and maximum power limitation are compared,and the allocation of computing resources by three algorithms is analyzed.It is concluded that the performance of ToRaT algorithm is better than that of the other two algorithms,which further confirms the effectiveness of the proposed algorithm.