Design And Implementation Of Iov Task Allocation Subsystem Based On Edge-End Collaboration

As an essential technology of intelligent transportation system,Internet of vehicles(IoV)is making transportation safer,more convenient and more intelligent.As a new distributed data processing and storage architecture,edge computing provides an effective computing task solution for Internet of vehicles.However,with the development of IoV technology,more and more application services emerge,resulting in massive pressure of real-time computing tasks.However,the computing capacity and memory space of edge computing nodes are relatively limited,which is difficult to ensure the completion of all tasks.Edge-end collaboration technology combines edge computing nodes with terminals with computing power,provide more sufficient,more flexible and closer computing power to users,and is more suitable for the calculation of realtime tasks.Therefore,it is important to apply the edge end collaboration architecture to the Internet of vehicles.However,the task allocation of vehicle networking under the edgeend collaborative architecture is more complex and more diverse.The problem of reasonably allocate real-time computing tasks needs to be studied.The existing related research often focuses on the edge end nodes,does not consider the computing power of the terminal nodes,and is weak in combination with the edge end collaborative architecture.The research work on the IoV practical application of task allocation algorithm is not deep enough,so it is difficult to effectively deal with and solve the task problem of the Internet of vehicles under the edge end collaborative architecture.In order to effectively solve the task allocation problem in this scenario,firstly,this paper proposes an Internet of vehicles task allocation architecture based on edge-end collaboration.In this architecture,considering task delay and overhead,task transmission model,task priority and the capacity of edge nodes and vehicle terminals,an Internet of vehicles task allocation model based on edge-end collaboration is established.In order to take into consideration the task type,task completion rate and task completion delay,task allocation utility is defined to evaluate the completion of tasks.Then,this paper describes the task allocation based on edge-end collaboration of IoV as an optimization problem.Based on greedy and quantum particle swarm optimization algorithm,a comprehensive task allocation algorithm is proposed to solve the problem.Simulation results show that compared with other task allocation methods,the strategy proposed in this paper has better effect and can effectively solve the task allocation problem in this scenario.What’s more,in order to more easily verify and practice the IoV task allocation strategy based on edge-end collaboration,and optimize the problems of poor scalability and high coupling of the existing task allocation module of the Internet of vehicles,this paper designs and develops a task allocation sub-system for the Internet of vehicles based on edge-end collaboration.This paper makes a detailed demand analysis and system design of the task allocation sub-system based on Vue.js framework and Spring Boot framework,and realize the functions of server node management,vehicle terminal management,task allocation,data visualization and so on.The system test results show that the task allocation sub-system designed and implemented in this paper can effectively give the allocation scheme of concurrent computing tasks in IoV,and meet the functional and performance requirements of the system.