Popularity-driven content caching

Suoheng Li, Jie Xu, Mihaela Van Der Schaar, Weiping Li

Research output: Chapter in Book/Report/Conference proceedingConference contribution

112 Scopus citations


This paper presents a novel cache replacement method - Popularity-Driven Content Caching (PopCaching). PopCaching learns the popularity of content and uses it to determine which content it should store and which it should evict from the cache. Popularity is learned in an online fashion, requires no training phase and hence, it is more responsive to continuously changing trends of content popularity. We prove that the learning regret of PopCaching (i.e., the gap between the hit rate achieved by PopCaching and that by the optimal caching policy with hindsight) is sublinear in the number of content requests. Therefore, PopCaching converges fast and asymptotically achieves the optimal cache hit rate. We further demonstrate the effectiveness of PopCaching by applying it to a movie.douban.com dataset that contains over 38 million requests. Our results show significant cache hit rate lift compared to existing algorithms, and the improvements can exceed 40% when the cache capacity is limited. In addition, PopCaching has low complexity.

Original languageEnglish (US)
Title of host publicationIEEE INFOCOM 2016 - 35th Annual IEEE International Conference on Computer Communications
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781467399531
StatePublished - Jul 27 2016
Event35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016 - San Francisco, United States
Duration: Apr 10 2016Apr 14 2016

Publication series

NameProceedings - IEEE INFOCOM
ISSN (Print)0743-166X


Other35th Annual IEEE International Conference on Computer Communications, IEEE INFOCOM 2016
Country/TerritoryUnited States
CitySan Francisco

ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

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