Optimized Adaptive Streaming Representations based on System Dynamics
Laura Toni, Ramon Aparicio-Pardo, Karine Pires, Gwendal Simon, Alberto, Blanc, and Pascal Frossard

TL;DR
This paper presents an optimization approach for adaptive streaming that improves user satisfaction and fairness by selecting encoding parameters based on network dynamics, content, and user characteristics.
Contribution
It introduces an integer linear programming model from the provider's perspective to optimize encoding rates for better adaptive streaming performance.
Findings
Outperforms vendor recommendations in user satisfaction and fairness.
Content and network constraints significantly impact encoding choices.
Practical guidelines for encoding parameter selection are proposed.
Abstract
Adaptive streaming addresses the increasing and heterogenous demand of multimedia content over the Internet by offering several encoded versions for each video sequence. Each version (or representation) has a different resolution and bit rate, aimed at a specific set of users, like TV or mobile phone clients. While most existing works on adaptive streaming deal with effective playout-control strategies at the client side, we take in this paper a providers' perspective and propose solutions to improve user satisfaction by optimizing the encoding rates of the video sequences. We formulate an integer linear program that maximizes users' average satisfaction, taking into account the network dynamics, the video content information, and the user population characteristics. The solution of the optimization is a set of encoding parameters that permit to create different streams to robustly…
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Taxonomy
TopicsImage and Video Quality Assessment · Peer-to-Peer Network Technologies · Network Traffic and Congestion Control
