基于收益感知的信息中心网络缓存机制

陈龙; 汤红波; 罗兴国; 柏溢; 张震

doi:10.11959/j.issn.1000-436x.2016101

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基于收益感知的信息中心网络缓存机制

学术论文 | 更新时间：2024-06-05

- 基于收益感知的信息中心网络缓存机制
- Gain-aware caching scheme for information-centric networking
- 通信学报 2016年37卷第5期页码：130-142
- 作者机构：
  
  国家数字交换系统工程技术研究中心，河南郑州450002
- 作者简介：
  
  [ "陈龙（1988-），男，山东济宁人，国家数字交换系统工程技术研究中心博士生，主要研究方向为信息中心网络、移动互联网。" ]
  [ "汤红波（1968-），男，湖北孝感人，国家数字交换系统工程技术研究中心教授、硕士生导师，主要研究方向为新型网络体系结构、移动通信网络。" ]
  [ "罗兴国（1951-），男，重庆人，国家数字交换系统工程技术研究中心教授、博士生导师，主要研究方向为移动通信网络、高效能计算机体系结构。" ]
  [ "柏溢（1975-），男，江苏盐城人，国家数字交换系统工程技术研究中心讲师，主要研究方向为信息中心网络、移动通信网络。" ]
  [ "张震（1985-），男，山东济宁人，国家数字交换系统工程技术研究中心讲师，主要研究方向为新型网络体系结构、信息中心网络。" ]
- 基金信息：
  
  国家自然科学基金资助项目(61372121);国家高技术研究发展计划（“863”计划）基金资助项目(2014AA01A701);国家科技重大专项基金资助项目(2013ZX03006003-009)
- DOI：10.11959/j.issn.1000-436x.2016101
  中图分类号： TP393
- 网络出版日期：2016-05，
  
  纸质出版日期：2016-05-15
- 稿件说明：
移动端阅览
陈龙, 汤红波, 罗兴国, 等. 基于收益感知的信息中心网络缓存机制[J]. 通信学报, 2016,37(5):130-142.

Long CHEN, Hong-bo TANG, Xing-guo LUO, et al. Gain-aware caching scheme for information-centric networking[J]. Journal on communications, 2016, 37(5): 130-142.
陈龙, 汤红波, 罗兴国, 等. 基于收益感知的信息中心网络缓存机制[J]. 通信学报, 2016,37(5):130-142. DOI： 10.11959/j.issn.1000-436x.2016101.

Long CHEN, Hong-bo TANG, Xing-guo LUO, et al. Gain-aware caching scheme for information-centric networking[J]. Journal on communications, 2016, 37(5): 130-142. DOI： 10.11959/j.issn.1000-436x.2016101.

摘要

针对信息中心网络（ICN）内置缓存系统中的海量内容块流行度获取和存储资源高效利用问题，以最大化节省内容访问总代价为目标，建立针对内容块流行度的缓存收益优化模型，提出了一种基于收益感知的缓存机制。该机制利用缓存对请求流的过滤效应，在最大化单点缓存收益的同时潜在地实现节点间协作和多样化缓存；使用基于布隆过滤器的滑动窗口策略，在检测请求到达间隔时间的同时兼顾从源服务器获取内容的代价，捕获缓存收益高的内容块。分析表明，该方法能够大幅压缩获取内容流行度的存储空间开销；仿真结果表明，该方法能够较为准确地实现基于流行度的缓存收益感知，且在内容流行度动态变化的情况下，在带宽节省和缓存命中率方面更具优势。

Abstract

The in-network caching system of information-centric networking had to deal with the popularity of huge number of content chunks and make efficient usage of storage resources.A content popularity based caching gain opti-mization model aimed to get maximum reduction of content retrieve cost was established

and a gain-aware caching scheme was proposed.By utilizing filtering effect of cache to request flow is scheme achieves caching cooperation and diversity potentially while maximizing caching gain of every single node.Bloom filter based sliding window strategy captures the content chunks with high caching gain according to request arrival interval and retrieval cost from the source.Analysis shows that the method can drastically reduce memory consumption caused by popularity monitoring.The simu-lation results illuminate that this scheme is well aware of content popularity based caching gain

and gets better band-width saving and cache hit ratio when content popularity is changing dynamically.

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references

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