Characterizing the file hosting ecosystem: A view from the edge
Performance Evaluation
Pytomo: a tool for analyzing playback quality of YouTube videos
Proceedings of the 23rd International Teletraffic Congress
YouTube everywhere: impact of device and infrastructure synergies on user experience
Proceedings of the 2011 ACM SIGCOMM conference on Internet measurement conference
A longitudinal view of HTTP video streaming performance
Proceedings of the 3rd Multimedia Systems Conference
Content and geographical locality in user-generated content sharing systems
Proceedings of the 22nd international workshop on Network and Operating System Support for Digital Audio and Video
Uncovering the big players of the web
TMA'12 Proceedings of the 4th international conference on Traffic Monitoring and Analysis
A case for a coordinated internet video control plane
Proceedings of the ACM SIGCOMM 2012 conference on Applications, technologies, architectures, and protocols for computer communication
A case for a coordinated internet video control plane
ACM SIGCOMM Computer Communication Review - Special october issue SIGCOMM '12
Network performance of smart mobile handhelds in a university campus WiFi network
Proceedings of the 2012 ACM conference on Internet measurement conference
Analyzing the impact of YouTube delivery policies on user experience
Proceedings of the 24th International Teletraffic Congress
Mapping the expansion of Google's serving infrastructure
Proceedings of the 2013 conference on Internet measurement conference
Benchmarking personal cloud storage
Proceedings of the 2013 conference on Internet measurement conference
Shedding light on the structure of internet video quality problems in the wild
Proceedings of the ninth ACM conference on Emerging networking experiments and technologies
Internet video delivery in youtube: from traffic measurements to quality of experience
DataTraffic Monitoring and Analysis
Characterizing Client Behavior of Commercial Mobile Video Streaming Services
Proceedings of Workshop on Mobile Video Delivery
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In this paper, we conduct a detailed study of the YouTube CDN with a view to understanding the mechanisms and policies used to determine which data centers users download video from. Our analysis is conducted using week-long datasets simultaneously collected from the edge of five networks - two university campuses and three ISP networks - located in three different countries. We employ state-of-the-art delay-based geolocation techniques to find the geographical location of YouTube servers. A unique aspect of our work is that we perform our analysis on groups of related YouTube flows. This enables us to infer key aspects of the system design that would be difficult to glean by considering individual flows in isolation. Our results reveal that while the RTT between users and data centers plays a role in the video server selection process, a variety of other factors may influence this selection including load-balancing, diurnal effects, variations across DNS servers within a network, limited availability of rarely accessed video, and the need to alleviate hot-spots that may arise due to popular video content.