Research On Network Access Technology Based On Fog Computing In The Edge Network

Today,smart cities are profoundly changing the way people live and manage their cities.The development of Intelligent Connected Vehicle can improve the social problems such as energy,environmental protection,safety,and congestion brought about by cars.The establishment of a new social transportation system and new smart cities is conducive to the construction of artificial intelligence,big data,robots,industrial Internet,and smart cities.Waiting for a number of trillionlevel industries is of strategic significance to the automobile industry's economy,society and the country.However,the current communication mechanism used in the vehicle cloud architecture and vehicle edge environment cannot meet the explosive growth of business requirements and application requirements for latency and fault tolerance.Therefore,this paper focuses on the vehicle fog calculation model in the vehicle-connected edge network,focuses on the network access part of the vehicle fog computing model,and proposes a network access algorithm based on fuzzy logic and ant colony optimization to select relay nodes to optimize The number of nodes is decreased,and the accuracy of connected nodes is improved.The main research work of this paper is as follows:(1)Aiming at the problems of the current vehicle cloud architecture and the communication mechanism used in the vehicle edge environment when working,the time delay is too high,the error rate is too large,etc.,a vehicle fog computing model based on edge computing is researched and the network connection in it The input section is optimized.This part is located in the fog node part of the fog calculation model.Each vehicle acts as a fog node.In order to reduce network congestion,a group of vehicles is selected as a relay node in each area to access the cloud server.The remaining vehicles communicate with the relay vehicles.At the same time,in order to make more efficient use of vehicle resources,this paper first selects candidate nodes through fuzzy logic,and then selects candidate nodes through an optimized ant colony algorithm with automatic pheromone backtracking,and selects effective nodes as relay nodes.The simulation results show that the number of nodes selected by the fuzzy logic and ant colony optimization methods is smaller,and the ratio of connected nodes is higher.(2)Aiming at the problems of high delay and low accuracy caused by the regular exchange of state information of vehicles in the vehicle fog architecture with the increasing number of vehicles today,a collective perception mechanism based on adaptive thresholds is proposed.While maintaining the correct level of perception,the beacon load is reduced,so that the state information can be transmitted more effectively between vehicles,and the accuracy of the received information of the perceived vehicle is judged through an adaptive threshold based on fuzzy logic.Simulation results show that the mechanism can reduce the beacon load and packet error rate for different vehicle densities to improve perception efficiency.