An optimized content caching strategy for video stream in edge-cloud environment

Abstract

With the mobile data traffic grows rapidly and the video data has a high proportion, the backhaul link faces great pressure. The conventional centralized architecture has been far from enough to satisfy the user demands. For reducing user response latency and easing backhaul stress, the streaming media contents should be proactively stored in the edge of network and new contents caching model needs to be presented. In this work, a video content collaborative caching strategy in the cloud-edge cooperative environment is proposed. In this strategy, first, the k-means algorithm is used to cluster the edge servers. Then the latency and caching cost gain bring by caching the content on the edge servers in the cluster and the collaborative cache domain are analyzed to establish the content caching problem. Further, the marginal gain is calculated by analyzing the latency and caching cost gain. Finally, in order to solve the content caching problem, this paper proposed a marginal gain based content caching algorithm. Experimental results prove the effectiveness of the proposed algorithm.