Modeling And Analysis Of Caching Strategy For Mobile Edge Services

With the development and application of industrial Internet technology,the Human-cyber-physical systems,as well as the popularization of a large number of smart with rich perception capabilities,and the exponential growth of mobile network traffic have brought huge challenges to mobile Internet technology.In the current cellular access network based on base stations,there will be a large delay from the base station to the remote server,and when a large amount of data is transmitted in the network,will lead to network congestion,while resulting in a waste of bandwidth resources,the user Poor experience and other issues.How to introduce edge caching technology in the mobile network,reduce the load of the service site,and effectively reduce the delay of user access is still an important issue to be solved urgently.This thesis focuses on how to improve the user's service experience and reduce the operating costs of service providers.From the perspective of the integration of Human-cyber-physical,this paper studies the user's interest preferences in the social space(human)and the cache content prediction of the information space(cyber)in the mobile edge environment.and physical space(physical)of the cache location to select the three aspects.First,the prediction methods of content popularity(What)and user preference(Who)are given,and then the mobile edge environment cache model is tested to find out where the content is stored(Where),and finally the method in the article is verified by experimental comparison.It can effectively improve the user experience and reduce the operating costs of the service provider.Firstly,a mobile edge caching method based on content popularity and user preferences is proposed,which improves the cache hit rate from two aspects of cached content and user preference prediction.On the one hand,the content popularity of the file is calculated by weighting the access time of the file and the number of accesses to predict the content of the cache;on the other hand,the clustering algorithm is used to classify users by calculating the time that users connect to the base station,and the user connection preference data set is constructed,and then based on User historical access data calculates file access probability for each type of user,and constructs user content preference data set.Secondly,build a mobile edge space model based on the mobile edge environment,describe the physical space by formal modeling,according to the label and content preferences of the user,construct a mobile environment the edge cache model,defines the lower edge of the mobile environment cooperating cache Changes Rules,use the method of model checking to traverse all the cache states,and according to the specific requirements of the user,give the system properties that meet the user's needs,and find out the cache location that meets the conditions.Finally,through the analysis of user access content types and content delivery process,the two performance indicators of access delay and backhaul link traffic are compared with the existing mobile edge caching methods.The results show that the caching strategy proposed in the article has a higher performance.Accuracy,you can get a better user experience.