沈皓珂;陈君;韩锐;

• 1:中国科学院声学研究所国家网络新媒体工程技术研究中心
• 2:中国科学院大学

摘要(Abstract)：

网内缓存是信息中心网络(ICN)的主要特征之一，是减小内容获取时延和提高网络资源利用率的重要环节。内容流行度越高，下一次请求时间越近，请求的次数越多，该内容价值就越大。针对海量缓存对象与有限缓存空间之间的矛盾，基于内容的“未来”价值，本文提出了一种基于价值预测的ICN缓存替换方法，结合内容流行度和新近频率值，构建内容价值预测模型，计算价值预测值，将“未来”价值最小的内容替换掉。仿真结果表明，本文提出的方法与最近最少使用、先进先出、随机替换等缓存替换方法相比，具有更高的缓存命中率，更低的请求响应时延。

关键词(KeyWords)： 网内缓存;信息中心网络;缓存替换;价值预测

Abstract:

Keywords:

基金项目(Foundation): 中国科学院战略性科技先导专项课题：SEANET技术标准化研究与系统研制(编号：XDC02070100)

作者(Authors): 沈皓珂;陈君;韩锐;

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