Research On Mobile Edge Caching Method Oriented To User QoS

With the increasingly frequent information interaction between humans,machines,and things,the use of Io T devices has increased dramatically,generating massive amounts of data at all times,which has brought great challenges to mobile edge networks.The surge in data volume of users makes the network pressure huge.Due to the limited data carrying capacity of the edge network,when a large amount of data is transmitted in the edge network,it will cause network congestion.In the current mobile edge environment,due to the user's strong mobility,data traffic is easily lost,the service quality is unstable,and the service requirements of the user's personalized requirements are difficult to guarantee.The introduction of edge caching technology in the mobile edge network can reduce the load on the service site and effectively reduce the delay of user access.This thesis focuses on how to improve the quality of service(QoS)in the user experience.From the perspective of services and users in the mobile edge environment,we study service-based cache location selection(Where)and cache content prediction(What),and user-based Three aspects of the cache strategy update(Who),specific methods of mobile edge caching are given,and experiments have verified that the method in the thesis can effectively improve the user experience,and finally designed and implemented a mobile edge cache service dispatch prototype system.1.How to choose a suitable cache base station based on the location of the service.First use clustering method to obtain user fitness value according to geographical location,and simplify location selection to matching problem,match user traffic data with edge base station energy,and find target cache base station;2.How to determine the specific cache content based on the content of the service.First use content popularity to predict hot cache content,then design base station caching algorithms to transform caching problems into NPhard optimization problems,integrate QoS gain,user interest,and maximize cache quality;3.How to recommend personalized caching strategies based on user needs.First,the user-side and server-side filtering methods are used,similarity clustering is used to update similar users and similar services,and then hybrid filtering is used to recommend similar services to similar users to ensure the stability and reliability of user service quality.Finally,the thesis designs and implements a mobile edge cache service dispatch prototype system.Based on user login information and requested service information,the system can intelligently select the appropriate edge cache service site for the requested service information,predict the relevant cache content,and update the user The cache strategy ensures that the user's QoS is maximized.