CPCDN : Content Delivery Powered by Context and User Intelligence

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review

25 Scopus Citations
View graph of relations

Author(s)

Detail(s)

Original languageEnglish
Article number6937177
Pages (from-to)92-103
Journal / PublicationIEEE Transactions on Multimedia
Volume17
Issue number1
Online published28 Oct 2014
Publication statusPublished - Jan 2015
Externally publishedYes

Abstract

There is an unprecedented trend that content providers (CPs) are building their own content delivery networks (CDNs) to provide a variety of content services to their users. By exploiting powerful CP-level information in content distribution, these CP-built CDNs open up a whole new design space and are changing the content delivery landscape. In this paper, we adopt a measurement-based approach to understanding why, how, and how much CP-level intelligences can help content delivery. We first present a measurement study of the CDN built by Tencent, a largest content provider based in China. We observe new characteristics and trends in content delivery which pose great challenges to the conventional content delivery paradigm and motivate the proposal of CPCDN, a CDN powered by CP-aware information. We then reveal the benefits obtained by exploiting two indispensable CP-level intelligences, namely context intelligence and user intelligence, in content delivery. Inspired by the insights learnt from the measurement studies, we systematically explore the design space of CPCDN and present the novel architecture and algorithms to address the new content delivery challenges that have arisen. Our results not only demonstrate the potential of CPCDN in pushing content delivery performance to the next level, but also identify new research problems calling for further investigation.

Research Area(s)

  • Content delivery, data mining, QoS, user behavior

Citation Format(s)

CPCDN : Content Delivery Powered by Context and User Intelligence. / Wang, Zhi; Zhu, Wenwu; Chen, Minghua; Sun, Lifeng; Yang, Shiqiang.

In: IEEE Transactions on Multimedia, Vol. 17, No. 1, 6937177, 01.2015, p. 92-103.

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journalpeer-review