Adaptive Content Management for UGC Video Delivery in Mobile Internet Era

The demand of storing and transferring user generated content (UGC) has been rapidly growing with the popularization of mobile devices equipped with video recording and playback capabilities. As a typical application of software-defined networks/network functions virtualization-based pervasive communications infrastructure, content delivery networks (CDNs) have been widely leveraged to distribute contents across different geographical locations. Nevertheless, the content delivery for UGC is inefficient with the existing “pull-based” caching mechanism in traditional CDNs, because there exists a huge volume of lukewarm or cold UGC which results in a low cache hit ratio. In this paper, we propose a “push-based” caching mechanism to efficiently and economically deliver UGC videos. Different from traditional CDNs which separate the original content storage and caching, we directly store UGC videos into selective servers which serve as both reliable storages and user-facing uploading servers. By carefully and dynamically selecting the storage locations of each UGC object based on its popularity and locality, we not only guarantee the data availability but also remarkably improve the content distribution performance and reduce the distribution cost.

[1]  Emin Gün Sirer,et al.  The design and implementation of a next generation name service for the internet , 2004, SIGCOMM.

[2]  Bernardo A. Huberman,et al.  Predicting the popularity of online content , 2008, Commun. ACM.

[3]  Jussara M. Almeida,et al.  Using early view patterns to predict the popularity of youtube videos , 2013, WSDM.

[4]  Yong-Yeol Ahn,et al.  Analyzing the Video Popularity Characteristics of Large-Scale User Generated Content Systems , 2009, IEEE/ACM Transactions on Networking.

[5]  Anne-Marie Kermarrec,et al.  Content and geographical locality in user-generated content sharing systems , 2012, NOSSDAV '12.

[6]  Zhi-Li Zhang,et al.  Vivisecting YouTube: An active measurement study , 2012, 2012 Proceedings IEEE INFOCOM.

[7]  Srinivasan Seshan,et al.  Developing a predictive model of quality of experience for internet video , 2013, SIGCOMM.

[8]  Jussi Kangasharju,et al.  Object replication strategies in content distribution networks , 2002, Comput. Commun..

[9]  Patrick Wendell,et al.  DONAR: decentralized server selection for cloud services , 2010, SIGCOMM '10.

[10]  Sandy Irani,et al.  Cost-Aware WWW Proxy Caching Algorithms , 1997, USENIX Symposium on Internet Technologies and Systems.

[11]  Gilbert Laporte,et al.  Exact algorithms for the joint object placement and request routing problem in content distribution networks , 2008, Comput. Oper. Res..

[12]  Konstantinos Psounis,et al.  Efficient randomized web-cache replacement schemes using samples from past eviction times , 2002, TNET.

[13]  Chen Tian,et al.  Optimizing cost and performance for content multihoming , 2012, SIGCOMM '12.