Real-time Vehicle And Cargo Matching And Path Optimization System Based On Cloud-side Collaboration

With the rapid development of cloud computing,Internet of Things and e-commerce,the combination of logistics and distribution with cloud computing technology,Internet of things technology,intelligent transportation and other new technologies has improved the distribution level of modern logistics.In the traditional car goods matching and path optimization system,mainly take the cloud data is the core of traditional cloud computing centralized processing mode,however,as the rapid growth of the number of all kinds of mobile devices and computing needs,traditional car goods matching and path optimization system will be faced with the network transmission delay,information is not timely response and vehicle cubed out low and path cost too high.Cloud-side collaboration uses the cooperation between the cloud and the edge to sink the edge segment to the user,providing data collection,data processing,data storage and other functions to meet the real-time requirements of users.Therefore,this paper studies the cloud-side collaboration technology and integrates it into the vehicle and cargo matching and path optimization system.The overall design of the system is carried out,and the overall efficiency of the system is improved through the design related algorithms,and the system is realized and tested.Firstly,in order to match the edge of cloud synergy used in car goods and path optimization system,this paper studies the related side of cloud synergy,car goods matching and path optimization model,designed a based on the cloud side car goods matching and path optimization model,presents the overall design,and the implementation of the model,mainly including data coordination,resource synergy and synergy,The realization of management coordination and service coordination,and the detailed design of resource coordination and data coordination algorithm,realize the vehicle and cargo matching and path optimization system of resources and data sharing,and respectively from efficiency,resource utilization and load balancing three aspects of experimental analysis proved that the model has good performance.Then,a real-time truck-goods matching and route optimization scheme is proposed,which is mainly applied to generate the initial distribution scheme and related routes in the cloud data center and feed back to users when carrying out cargo matching and route recommendation for vehicles.Due to the matching of vehicles and goods,there will be vehicles with low loading rate.In the transportation process of such vehicles,the cloud data center will upload vehicle information to the edge end,and the edge end will sort users according to the priority of users and the loading rate of vehicles.The edge terminal receives real-time cargo information and real-time vehicle information,and makes real-time distribution scheme and route recommendation for users who can carry out secondary distribution.This paper proposes relevant algorithms and pseudo-code implementation process for each stage,and designs experiments to prove the feasibility and superiority of the scheme from three aspects of user waiting time,vehicle loading rate and path cost.Finally,the above model and scheme are applied to the vehicle and cargo matching and path optimization system,and the main functional modules of the system are displayed and tested.The test results show that the system can meet the real-time user needs in terms of time and cost.