关键词: 流式应用, 用户行为, 缓存策略, 按需加载

Abstract:

In current streaming application distribution system, the client loads application resources on demand through streaming loading, so the client needs to frequently access the remote server, which causes problems such as server overload, increased traffic consumption and slow application startup. Aiming at the above problems, the cache and integrated user behavior prediction strategy A-RBFS（Adaptive Recently Behavior Frequently Size） of the streaming application distribution system is proposed. The strategy considers the factors such as user usage behavior, client state and application size, and adjusts the total size of the cache space according to the size of the remaining storage space of the client. The implementation results show that under the same conditions, the cache replacement strategy is significantly better than the LRU and LFU cache replacement strategies.

Key words: streaming application, user behavior, cache strategy, load on demand