内容中心网络中一种基于内容扩散的主动缓存机制

借鉴分子扩散的思想，提出一种基于内容扩散的主动缓存机制（Content Diffusion Based Proactive Caching, CDBPC).该机制引入缓存内容浓度的概念来描述不同内容在不同区域内的需求程度，然后根据节点间的缓存内容浓度关系来驱动内容副本在网络中的主动推进和迁移，并结合内容的流行度等因素实现了缓存内容的概率性放置，从而达到内容缓存的快速部署和推进，提高为用户提供就近响应概率的目的.仿真结果表明，该机制能有效地降低系统的平均接入代价并提高缓存命中率.
This paper borrowed the idea of molecular diffusion and proposed a proactive caching scheme based on content diffusion. In this mechanism, the conception of content concentration was introduced to analyze user demands for different contents in different network regions. In order to achieve fast content placement and increase the probability of providing responses to user requests by the nearer caching nodes, the content replicas were proactively pushed forward or migrated according to the content concentration difference between nodes. Furthermore, by synthetically considering the content popularity, a probabilistic content placement method was also implemented. The simulation results have shown that this scheme can effectively decrease the average access cost and improve the cache hit ratio.