关键词: 边缘缓存, 用户中心访问行为, 多臂算法, 缓存击中率

Abstract: In order to overcome the shortcomings of the current caching strategy which fails to predict the popularity of short-term hot content sets and cold content sets, this paper proposes a Multi-Arm bandit caching algorithm based on Central Behavior（MACB）. MACB narrows the scope of user group preference by using user central behavior, and then learns the popularity of short-term hot content sets and cold content sets effectively throughout exploration and exploitation process. When applied to China Mobile User Data Record（UDR） data set, MACB makes a hit rate lift compared to the contrast caching strategy, and its effectiveness is shown.

Key words: edge caching, central behavior, multi-arm bandit, hit rate