中国邮电高校学报(英文) ›› 2013, Vol. 20 ›› Issue (5): 45-50.doi: 10.1016/S1005-8885(13)60088-6

• Networks • 上一篇    下一篇

Fast convergence caching replacement algorithm based on dynamic classification for content-centric networks

方超,黄韬,刘江,刘韵洁   

  1. Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • 收稿日期:2013-03-19 修回日期:2013-06-05 出版日期:2013-10-30 发布日期:2013-10-29
  • 通讯作者: 方超 E-mail:fangchao@bupt.edu.cn
  • 基金资助:
    This work was supported by the National Basic Research Program of China (2012CB315801, 2011CB302901), the Fundamental Research Funds for the Central Universities (2013RC0113).

Fast convergence caching replacement algorithm based on dynamic classification for content-centric networks

  1. Key Laboratory of Universal Wireless Communications, Ministry of Education, Beijing University of Posts and Telecommunications, Beijing 100876, China
  • Received:2013-03-19 Revised:2013-06-05 Online:2013-10-30 Published:2013-10-29
  • Contact: fang chao E-mail:fangchao@bupt.edu.cn
  • Supported by:
    This work was supported by the National Basic Research Program of China (2012CB315801, 2011CB302901), the Fundamental Research Funds for the Central Universities (2013RC0113).

摘要: One of the key research fields of content-centric networking (CCN) is to develop more efficient cache replacement policies to improve the hit ratio of CCN in-network caching. However, most of existing cache strategies designed mainly based on the time or frequency of content access, can not properly deal with the problem of the dynamicity of content popularity in the network. In this paper, we propose a fast convergence caching replacement algorithm based on dynamic classification method for CCN, named as FCDC. It develops a dynamic classification method to reduce the time complexity of cache inquiry, which achieves a higher caching hit rate in comparison to random classification method under dynamic change of content popularity. Meanwhile, in order to relieve the influence brought about by dynamic content popularity, it designs a weighting function to speed up cache hit rate convergence in the CCN router. Experimental results show that the proposed scheme outperforms the replacement policies related to least recently used (LRU) and recent usage frequency (RUF) in cache hit rate and resiliency when content popularity in the network varies.

关键词: CCN, cache replacement policy, dynamic classification, fast convergence, category popularity

Abstract: One of the key research fields of content-centric networking (CCN) is to develop more efficient cache replacement policies to improve the hit ratio of CCN in-network caching. However, most of existing cache strategies designed mainly based on the time or frequency of content access, can not properly deal with the problem of the dynamicity of content popularity in the network. In this paper, we propose a fast convergence caching replacement algorithm based on dynamic classification method for CCN, named as FCDC. It develops a dynamic classification method to reduce the time complexity of cache inquiry, which achieves a higher caching hit rate in comparison to random classification method under dynamic change of content popularity. Meanwhile, in order to relieve the influence brought about by dynamic content popularity, it designs a weighting function to speed up cache hit rate convergence in the CCN router. Experimental results show that the proposed scheme outperforms the replacement policies related to least recently used (LRU) and recent usage frequency (RUF) in cache hit rate and resiliency when content popularity in the network varies.

Key words: CCN, cache replacement policy, dynamic classification, fast convergence, category popularity