HD: A Cache Storage Strategy Based on Hierarchical Division in Content-centric Networking

Zongming Feng, Jun Yu Li, Haibo Wu, Jiang Zhi
{"title":"HD: A Cache Storage Strategy Based on Hierarchical Division in Content-centric Networking","authors":"Zongming Feng, Jun Yu Li, Haibo Wu, Jiang Zhi","doi":"10.1109/CSE.2014.123","DOIUrl":null,"url":null,"abstract":"As a promising direction of future Internet, Content-Centric Network (CCN) has attracted world-wide attention. In-network caching is an important feature of CCN network, which has significant impacts on the performance of content transmission. Existing researches on in-network caching either have no regard for the collaboration or need giant additional overhead for global optimization. This paper proposes a hierarchical division-based cache storage strategy, called HD, which allows the contents can be cached in different nodes by grouping contents into different hierarchies. HD aims to reduce propagation delay and server load by light-weight collaboration mechanisms that allows the popular contents could be cached along the path with certain a probability. The performance of HD scheme was evaluated by comparing with the well-known schemes through simulation. The experimental results indicate that HD strategy can save up to 30.77% hop reduction ratio, 44.93% average cache hit ratio and 11.88% server hit ratio while the parameter α of Zipf distribution is increasing.","PeriodicalId":258990,"journal":{"name":"2014 IEEE 17th International Conference on Computational Science and Engineering","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 IEEE 17th International Conference on Computational Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CSE.2014.123","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1

Abstract

As a promising direction of future Internet, Content-Centric Network (CCN) has attracted world-wide attention. In-network caching is an important feature of CCN network, which has significant impacts on the performance of content transmission. Existing researches on in-network caching either have no regard for the collaboration or need giant additional overhead for global optimization. This paper proposes a hierarchical division-based cache storage strategy, called HD, which allows the contents can be cached in different nodes by grouping contents into different hierarchies. HD aims to reduce propagation delay and server load by light-weight collaboration mechanisms that allows the popular contents could be cached along the path with certain a probability. The performance of HD scheme was evaluated by comparing with the well-known schemes through simulation. The experimental results indicate that HD strategy can save up to 30.77% hop reduction ratio, 44.93% average cache hit ratio and 11.88% server hit ratio while the parameter α of Zipf distribution is increasing.
内容中心网络中基于分层划分的高速缓存存储策略
内容中心网络(Content-Centric Network, CCN)作为未来互联网发展的一个重要方向,受到了世界各国的广泛关注。网络内缓存是CCN网络的一个重要特性,它对内容传输的性能有着重要的影响。现有的网络内缓存研究要么不考虑协作,要么需要大量的额外开销来进行全局优化。本文提出了一种基于层次划分的高速缓存存储策略HD,该策略通过将内容分组到不同的层次来实现对不同节点上内容的缓存。HD旨在通过轻量级协作机制减少传播延迟和服务器负载,该机制允许热门内容以一定的概率沿路径缓存。通过仿真比较,对HD方案的性能进行了评价。实验结果表明,在Zipf分布参数α不断增大的情况下,HD策略的跳降率可达30.77%,平均缓存命中率可达44.93%,服务器命中率可达11.88%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 求助全文
来源期刊
自引率
0.00%
发文量
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信