Popularity-aware cloud-edge collaborative caching strategy for wireless video
Mobile edge caching technology caches videos at edge servers closer to users,thereby providing users with more convenient services.Current video caching methods rely primarily on overall video popularity,ignoring the spatial and temporal variations in video popularity.As a result,they fail to fully utilize the wide geographical distribution characteristics of edge servers,thereby impacting the effectiveness of video caching in the cloud-edge environment.In order to address this issue,we propose a wireless video cloud edge caching strategy based on popularity perception.First,based on the cloud-edge collaborative architecture,we establish a cloud-edge video caching model that takes into account the spatial and temporal variations in video popularity.This model combines video segmentation and video segment popularity,and aims to minimize the average delay for all videos requested and maximize the total cache hit rate.Second,considering the limited computational and caching resources of edge servers,we propose a caching strategy called Global Value Evaluation(GVE).This strategy quantifies the ability of a video segment to fulfill user requests as its caching value and incorporates a caching value penalty mechanism to dynamically assess the value of cached content,enabling efficient caching of video segments.Finally,simulation experiments demonstrate that the proposed strategy can significantly reduce the average transmission delay and backhaul traffic load,and improve the cache hit rate of requested videos.
mobile edge computingvideo on demandvideo cachecloud-edge collaborationvideo popularity
万方数据
维普
