An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP
MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
Dissecting Video Server Selection Strategies in the YouTube CDN
ICDCS '11 Proceedings of the 2011 31st International Conference on Distributed Computing Systems
Network characteristics of video streaming traffic
Proceedings of the Seventh COnference on emerging Networking EXperiments and Technologies
What happens when HTTP adaptive streaming players compete for bandwidth?
Proceedings of the 22nd international workshop on Network and Operating System Support for Digital Audio and Video
Confused, timid, and unstable: picking a video streaming rate is hard
Proceedings of the 2012 ACM conference on Internet measurement conference
A comparative study of android and iOS for accessing internet streaming services
PAM'13 Proceedings of the 14th international conference on Passive and Active Measurement
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HTTP Adaptive Streaming dominates most of the traffic on the Internet today and a large fraction is driven by video consumption on mobile phones and tablet devices. The client player implementations from different popular commercial services make different parameter and architectural choices, which result from heterogeneous APIs and device limitations. As a result, they exhibit quite different behaviors even for the same service, with very different traffic consumption characteristics. In this paper, we examine three major streaming services -- Netflix, Youtube, and Hulu, over the two dominant mobile platforms -- iOS and Android, in order to understand the impact of these design choices. We infer detailed session behavior based on passively collected packet traces over a large set of experiments across the providers and network types. We discover varying amounts of "redundant" traffic in the presence of bandwidth adaptation across the services, which negatively impacts network resources. We also find these design choices lead to unfairness in bandwidth consumption on shared networks across different platforms. In particular, we find the Android Netflix player is able to take a larger fraction of shared bandwidth when competing with the iOS implementation.