Poster: A Content Popularity Classification-Based Content Search Scheme for CCN
Yurino Sato, Hiroyuki Koga · 2022
This paper presents a novel content search scheme based on classified content popularity for CCN. Some existing research focuses mainly on improving the cache hit rate to resolve the on-path caching problem. We decide this problem by reducing acquisition hops to obtain requested contents. Our proposed scheme can reduce the number of acquisition hops by determining the forwarding range of search packets using classified content popularity calculated on each CR. In this paper, we clarify that the proposed scheme reduces the number of acquisition hops by up to 10% compared to previous work through simulation evaluation.