The Akamai network: a platform for high-performance internet applications
ACM SIGOPS Operating Systems Review
Dynamic adaptive streaming over HTTP --: standards and design principles
MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
An experimental evaluation of rate-adaptation algorithms in adaptive streaming over HTTP
MMSys '11 Proceedings of the second annual ACM conference on Multimedia systems
QDASH: a QoE-aware DASH system
Proceedings of the 3rd Multimedia Systems Conference
An experimental evaluation of rate-adaptive video players over HTTP
Image Communication
Improving fairness, efficiency, and stability in HTTP-based adaptive video streaming with FESTIVE
Proceedings of the 8th international conference on Emerging networking experiments and technologies
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Adaptive streaming addresses the increasing and heterogenous demand of multimedia content over the Internet by offering several streams for each video. Each stream has a different resolution and bit rate, aimed at a specific set of users, e.g., TV, mobile phone. While most existing works on adaptive streaming deal with optimal playout-control strategies at the client side, in this paper we concentrate on the providers' side, showing how to improve user satisfaction by optimizing the encoding parameters. We formulate an integer linear program that maximizes users' average satisfaction, taking into account the network characteristics, the type of video content, and the user population. The solution of the optimization is a set of encoding parameters that outperforms commonly used vendor recommendations, in terms of user satisfaction and total delivery cost. Results show that video content information as well as network constraints and users' statistics play a crucial role in selecting proper encoding parameters to provide fairness among users and reduce network usage. By combining patterns common to several representative cases, we propose a few practical guidelines that can be used to choose the encoding parameters based on the user base characteristics, the network capacity and the type of video content.