I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
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Youtube traffic characterization: a view from the edge
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Analyzing video services in Web 2.0: a global perspective
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YouTube traffic dynamics and its interplay with a tier-1 ISP: an ISP perspective
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User-aware energy efficient streaming strategy for smartphone based video playback applications
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Internet video delivery in youtube: from traffic measurements to quality of experience
DataTraffic Monitoring and Analysis
Improving Fairness, Efficiency, and Stability in HTTP-Based Adaptive Video Streaming With Festive
IEEE/ACM Transactions on Networking (TON)
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In this paper we present a complete measurement study that compares YouTube traffic generated by mobile devices (smart-phones,tablets) with traffic generated by common PCs (desktops, notebooks, netbooks). We investigate the users' behavior and correlate it with the system performance. Our measurements are performed using unique data sets which are collected from vantage points in nation-wide ISPs and University campuses from two countries in Europe and the U.S. Our results show that the user access patterns are similar across a wide range of user locations, access technologies and user devices. Users stick with default player configurations, e.g., not changing video resolution or rarely enabling full screen playback. Furthermore it is very common that users abort video playback, with 60% of videos watched for no more than 20% of their duration. We show that the YouTube system is highly optimized for PC access and leverages aggressive buffering policies to guarantee excellent video playback. This however causes 25%-39% of data to be unnecessarily transferred, since users abort the playback very early. This waste of data transferred is even higher when mobile devices are considered. The limited storage offered by those devices makes the video download more complicated and overall less efficient, so that clients typically download more data than the actual video size. Overall, this result calls for better system optimization for both, PC and mobile accesses.