Research On Efficient Scheduling Mechanism Of Vehicle Network Based On Edge Computing

With the rapid development of mobile communication and the Internet,VANET has become an indispensable part of the urban intelligent transportation system,and has a wide range of application scenarios in the fields of traffic scheduling,traffic monitoring,danger warning,and vehicle information interaction.At present,the traffic congestion problem in large cities is becoming more and more serious,causing huge economic losses to the society and causing serious environmental pollution.Therefore,how to use the characteristics of VANET workshop communication to design an effective traffic congestion scheduling mechanism to alleviate traffic congestion is one of the current research hotspots.At the same time,due to the limited computing resources of the vehicle itself,when the vehicle generates a large number of tasks to be processed,how to use VANET for efficient task offloading strategy to reduce the average response delay of the task,and provide users with low-latency and high-quality services,is also an urgent problem to be solved.Aiming at the above problems,this paper combines VANET with edge computing to make full use of the characteristics of low-latency and real-time decision-making of edge computing,and studies the efficient scheduling mechanism of vehicle network based on edge computing.The main research work of this paper is as follows:（1）This paper proposes an efficient traffic congestion scheduling mechanism（ETCS）based on edge computing,which is used to quickly solve the congestion caused by vehicle traffic accidents.In this mechanism,this paper designs a three-layer system structure,and the main computational tasks are placed in the RSU in the edge computing layer to reduce the system response delay.Then,a method for actively detecting and distributing traffic accidents is designed.When a traffic accident occurs,the accident vehicle will immediately generate an alert message containing the information of the accident location,and send it to the nearby RSU to predict the congestion of the vehicle,thereby improving the congestion handling.On this basis,in order to calculate a new alternative route for vehicles in the congested area,this paper designs a rerouting algorithm based on probability selection function.The algorithm can select a new route for the vehicle from the K alternative paths,which reduces the possibility of congestion transfer and optimizes the congestion of the overall road traffic network.Finally,the OMNeT++simulation platform verifies that the mechanism can effectively reduce the average vehicle travel time,fuel consumption,and CO₂ emissions.（2）This paper proposes an terminal-edge collaborative task offloading mechanism（TCTO）,which fully dispatches the vehicle’s own processing capability and edge computing capability to reduce the average response delay of task offloading.In this work,the paper models the computational and communication overheads of the vehicle and edge,respectively,and establishes a mathematical model that minimizes the average response delay of task offloading.On this basis,through theoretical analysis,the solution objective is transformed into the best perfect matching problem of bipartite graph.Then a bipartite matching algorithm based on dinic method（DBM）is designed to solve the problem.The experimental results show that the TCTO mechanism proposed in this paper has achieved good results in minimizing the delay of task response.