Distributing Layered Encoded Video through Caches
IEEE Transactions on Computers
A Comparison of Bandwidth Smoothing Techniques for the Transmission of Prerecorded Compressed Video
INFOCOM '97 Proceedings of the INFOCOM '97. Sixteenth Annual Joint Conference of the IEEE Computer and Communications Societies. Driving the Information Revolution
A framework for encoding and caching of video for quality adaptive progressive download
Proceedings of the 15th international conference on Multimedia
I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Youtube traffic characterization: a view from the edge
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Computer Networks: The International Journal of Computer and Telecommunications Networking
Workload generation for YouTube
Multimedia Tools and Applications
Perspectives on quality of experience for video streaming over WiMAX
ACM SIGMOBILE Mobile Computing and Communications Review
Buffer management mechanism suitable for TCP streaming in QoS-aware IP router
CCNC'10 Proceedings of the 7th IEEE conference on Consumer communications and networking conference
QoE-Oriented performance evaluation of video streaming over WiMAX
WWIC'10 Proceedings of the 8th international conference on Wired/Wireless Internet Communications
IEEE Communications Surveys & Tutorials
Adaptive media playout for low-delay video streaming over error-prone channels
IEEE Transactions on Circuits and Systems for Video Technology
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Established in 2005, YouTube is one of the fastest-growing websites, and has become one of the most accessed sites in the Internet. It has a significant impact on the Internet traffic distribution, but itself is suffering from severe scalability constraints and quality of service. Understanding the features of YouTube is thus crucial to network traffic engineering and to sustainable development of this new generation of services. In this survey, we first present an overview of previous works and analysis on YouTube with a particular attention on Quality of Experience. We then describe how the increased availability of meta-data in Web 2.0 (e.g., popularity distribution of video clips) could be effectively exploited to improve the performance and scalability of YouTube. In particular, we study the benefit gained by local caching along with prefetching in terms of reducing the client access time and start up delay in watching video.