Mobile Edge Data Cooperative Cache Admission Based on Content Popularity

Edge computing provides more rapid and convenient services to the user by deploying computing resources and storage resources on network edges closer to the user. However, the edge server has small storage capacity, irregular user requests and real-time changes in user preferences. To address these problems, this paper presents a Mobile Edge Data Cooperative Cache Admission Based on Content Popularity (DCCCP) based on the perspective of the content provider. First, we analyze and learn the key feature properties of video objects to build the tree data structure and dynamically adjust the tree structure according to the state of the leaf nodes. Next, the multiarm bandit model is considered for the tree structure characteristics and the number of samples. In addition, considering the limited edge server capacity and the large cloud-edge transmission latency, edge collaboration is used for data cache. Finally, we experiment the DCCCP algorithm with four excellent algorithms in terms of hit rate, latency and system cost, and demonstrate the effectiveness of the DCCCP algorithm.