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首页> 外文期刊>Journal of the National Institute of Information and Communications Technology >Local Tree Hunting Scheme to Find the Closest Content in In-Network Cache
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Local Tree Hunting Scheme to Find the Closest Content in In-Network Cache

机译:本地树搜寻方案以查找网络内缓存中最接近的内容

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摘要

CCN/ICN with in-network cache capability has been expected as Future Internet. This paper proposes a novel content discovery scheme called Local Tree Hunting for cached contents. It provides almost the same hunting performance as the entire hunting although the hunting area is localized into a tree whose root is the node with caching history. As an option, when caching the state is notified to neighbor nodes to make a short-cut of request forwarding. The effectiveness of the proposed scheme is verified with computer simulation with a Zipf s law content popularity distribution and the Least Recently Used eviction model.
机译:具有网络内缓存功能的CCN / ICN有望成为未来的互联网。本文针对缓存的内容提出了一种新的内容发现方案,称为本地树搜索。它提供了与整个狩猎几乎相同的狩猎性能,尽管狩猎区域位于一棵树中,该树的根是具有缓存历史记录的节点。作为一种选择,在缓存时,将状态通知给邻居节点,以进行请求转发的捷径。通过计算机模拟,采用Zipf法则的内容受欢迎程度分布和最近最少使用的逐出模型,验证了该方案的有效性。

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