一种基于SDN的CCN集中控制缓存决策方法

曲桦; 李岩松; 刘军; 赵季红; 郭涯

doi:10.11959/j.issn.1000−0801.2017132

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一种基于SDN的CCN集中控制缓存决策方法

研究与开发 | 更新时间：2024-06-05

- 一种基于SDN的CCN集中控制缓存决策方法
- A method of CCN centralized control cache decision based on SDN
- 电信科学 2017年33卷第5期页码：12-20
- 作者机构：
  
  1. 西安交通大学，陕西西安 710049
  2. 西安邮电大学，陕西西安 710061
- 作者简介：
  
  [ "曲桦（1961−），男，博士，西安交通大学教授、博士生导师，主要研究方向为现代通信网、计算机网络体系结构。" ]
  [ "李岩松（1992−），男，西安交通大学硕士生，主要研究方向为基于软件定义网络的内容中心网络及其缓存策略。" ]
  [ "刘军（1989−），男，西安交通大学硕士生，主要研究方向为基于软件定义网络的内容中心网络及其缓存策略。" ]
  [ "赵季红（1963−），女，博士，西安交通大学、西安邮电大学教授，主要研究方向为宽带通信网、新一代网络的管理与控制。" ]
  [ "郭涯（1991−），男，西安交通大学博士生，主要研究方向为软件定义网络、网络虚拟化。" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61371087);国家自然科学基金资助项目;The National Natural Science Foundation of China(61531013);教育部—中国移动科研基金资助项目;Joint Research Foundation of Ministry of Education and China Mobile(MCM20150102)
- DOI：10.11959/j.issn.1000−0801.2017132
  中图分类号： TN915.9
- 网络出版日期：2017-05，
  
  纸质出版日期：2017-05-15
- 稿件说明：
移动端阅览
曲桦, 李岩松, 刘军, 等. 一种基于SDN的CCN集中控制缓存决策方法[J]. 电信科学, 2017,33(5):12-20.

Hua QU, Yansong LI, Jun LIU, et al. A method of CCN centralized control cache decision based on SDN[J]. Telecommunications science, 2017, 33(5): 12-20.
曲桦, 李岩松, 刘军, 等. 一种基于SDN的CCN集中控制缓存决策方法[J]. 电信科学, 2017,33(5):12-20. DOI： 10.11959/j.issn.1000−0801.2017132.

Hua QU, Yansong LI, Jun LIU, et al. A method of CCN centralized control cache decision based on SDN[J]. Telecommunications science, 2017, 33(5): 12-20. DOI： 10.11959/j.issn.1000−0801.2017132.

摘要

在软件定义网络（SDN）和内容中心网络（CCN）融合架构下，为了充分利用控制层对网络拓扑和缓存资源的全局感知，在全网中实现缓存资源的优化使用，提出了一种集中控制的缓存决策优化方案。在该方案中，应用粒子群优化算法（PSO）并且根据节点边缘度、节点重要度以及内容流行度对缓存资源和内容进行集中缓存决策，使得内容在不同的节点进行合理的缓存。仿真结果表明，通过评估缓存大小对缓存性能的影响，PSO缓存决策方法取得了比LCE、PROB缓存决策策略更优的缓存命中率和路径延展率，明显降低了缓存节点的缓存替换数，使得缓存达到了整体缓存优化。

Abstract

In the software defined networking and content centric networking integration framework

a cache optimi-zation scheme of centralized control was proposed to make full use of global awareness of the control layer for net-work topology and cache resources

and achieve the optimal use of caching resources in the entire network.In this scheme

the particle swarm optimization (PSO) was applied for centralized cache decision-making depending on node edge degree

node importance degree and content popularity.Therefore

the contents were cached in different nodes reasonably.Simulation result shows that the proposed PSO caching scheme achieves larger cache hit rate and lower path stretch than that of LCE scheme

PROB scheme by evaluating the impact of cache size and content popularity on the caching performance.It also shows that PSO scheme significantly reduces the number of cache nodes to replace the cache

making the cache to achieve the overall cache optimization.

关键词

Keywords

references

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