Design And Implementation Of "let's Run" Campus Application System Based On Cloud Platform

In recent years,with the increasing demand for "short-distance" business by college teachers and students,the "last mile" model of the campus application platform has been rapidly promoted and used.In order to solve the problems of high concurrent access and elastic expansion of system computing resources,this paper combines the Iaa S features of the Open Stack cloud computing platform to design the system,and realizes the functions of order release,order recommendation,data prediction and other functions of "Let's Run" campus application system.The main work of this article is as follows:(1)The demand analysis and design for the "Let's Run" platform.First,conduct questionnaire surveys on different colleges,analyze the questionnaires and extract system requirements;Second,use UML modeling tools such as use case diagrams,timing diagrams,activity diagrams to perform system use case analysis and system function modeling;Finally complete the overall architecture design of the system,Function module design,database design and RESTful API design.(2)Design Sunnychaser framework and coding to achieve system functions.The Sunnychaser framework adopts MVC development ideas and open source Python,Android,vue.js,Nginx and other technologies to make the system more scalable."Let's Run" campus application system is based on this framework coding to realize the functions of order release,user orders,recommendation,management,data analysis,data prediction and so on.(3)Research and application of content-based recommendation algorithm to achieve order recommendation.First,create the 01 matrix and user profile for the completed orders of the user and the system's alternative recommended order sets;Second,use the improved Pearson correlation coefficient to calculate the similarity between the user portrait and the order portrait;Finally,obtain candidate Top N order recommendation sets with a highe similarity to implement system order recommendation.(4)Research and application of ARMA model to realize the system data prediction function.First,according to the functional requirements to pre-process thedata,check the stationarity and non-white noise,order the p and q parameters of the ARMA model.Second,construct the ARMA model and predict the data;Finally,test the ARMA model and display the prediction result on the front of the system.(5)Construction and application of cloud platform.In order to better deploy the“Let's Run” campus application system on the public cloud platform,this article builds a private Openstack cloud platform and a public Alibaba Cloud platform;The second is to verify the Open Stack cloud platform and Alibaba Cloud platform on-demand use,elastic expansion,load balancing and other characteristics;finally,the "Let's Run" campus application system is deployed on the cloud platform.The “Let's Run” campus application system has been designed,developed,deployed and tested in the cloud,and trial-run on the campus of Guizhou University.It has achieved the expected functions and currently running good condition.