by Denny Stohr, Alexander Frömmgen, Amr Rizk, Michael Zink, Ralf Steinmetz and Wolfgang Effelsberg
Dynamic Adaptive Streaming over HTTP (DASH) aims to constantly provide high user quality of experience in dynamically changing network environments. The heterogeneity of the streaming environment makes many of the developed DASH algorithms possess performance affinities that we denote as sweet spots.
We show the substantial impact of the video player choice and its configuration on the streaming performance. We systematically examine three established open-source DASH players, i.e., DASH.JS, Google’s Shaka Player, and AStream, that implement fundamentally different configurations featuring various adaptation algorithms.
We establish a large scale emulation framework to (i) extract player sweet spots and (ii) achieve a direct, reproducible comparison of real-world DASH players and algorithms. In the following we show empirical evidence (exerpts from the paper) demonstrating that an isolated analysis of DASH player modules is insufficient to capture the player streaming performance.
One of the major observations in this paper is that the choice of the adaptation algorithm is dominated by the choice of the player and its configuration.
All players and adaptation algorithms are represented on the Pareto frontier such that no single player / configuration dominates.
To enable other researchers to reproduce and build on our work, we provide our evaluation framework.
Setup a new DASH simulation study
Analyse your DASH simulation study
Can be downloaded here
Extract the source, e.g.,
tar -zxvf acm-maci-dash.tar.gz
and follow the instructions in
The MACI Frontend:
Attached (logs visible)
docker-compose up --build maci-backend
docker-compose up -d --build maci-backend
The MACI Worker:
vagrant up --provision