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CAdViSE: Cloud based Adaptive Video Streaming Evaluation Framework for the Automated Testing of Media Players

The document discusses 'cadvise', a cloud-based framework designed for automated testing of media players under varying network conditions. It includes components for application scripting, cloud infrastructure, and analytics, allowing for the evaluation of how different media players handle streaming challenges. The framework includes experiments with three media players and provides analytics for assessing their performance and identifying improvement areas.

Technology◦
CAdViSE: Cloud-based Adaptive Video Streaming Evaluation Framework for the Automated Testing of Media Players Babak Taraghi, Anatoliy Zabrovskiy, Christian Timmerer*, Hermann Hellwagner Institute of Information Technology Universität Klagenfurt, *Bitmovin Austria 2020
Introduction and Motivation CAdViSE: Cloud-based Adaptive Video Streaming Evaluation Framework for the Automated Testing of Media Players MMSys ’20, June 8–11, 2020, Istanbul, Turkey • Evaluate how a media player can adopt the stream attributes to ups and downs of a real network conditions • Mimic the real-life internet connections quality (latency, packet drops, available bandwidth and packet corruptions) • Integratable with common CI/CD pipelines • Visualize the results with diagrams and compare the statistical results for multiple media players • Using cloud infrastructure with automated deployment instead of running on bare-metal machines
Proposed Solution Three main components or modules: 1. Application; i. Runner script ii. Initializer script iii. Starter script 2. Cloud infrastructure; i. Player container (VNC and Selenium) ii. Network emulator iii. EC2, SSM, S3 and CloudWatch 3. Analytics; i. Bitmovin Analytics plugin for players ii. Bitmovin Analytics dashboard CAdViSE: Cloud-based Adaptive Video Streaming Evaluation Framework for the Automated Testing of Media Players MMSys ’20, June 8–11, 2020, Istanbul, Turkey
Experiments and Results • 5 Experiments, 9:00 minutes each • t2.medium EC2 instances (4Gib RAM, 2 CPU cores) • Using three players: – Bitmovin Player – Shaka Player – Dash.js Player • Emulated network: a. 4 mbit/s b. 800 kbit/s c. 4 mbit/s CAdViSE: Cloud-based Adaptive Video Streaming Evaluation Framework for the Automated Testing of Media Players MMSys ’20, June 8–11, 2020, Istanbul, Turkey
Experiments and Results • Bitmovin Analytics Dashboard – Important metrics to be compared easily for all tested media players – Showing clues of what could go wrong in each player for most users – What are the improvable points for players CAdViSE: Cloud-based Adaptive Video Streaming Evaluation Framework for the Automated Testing of Media Players MMSys ’20, June 8–11, 2020, Istanbul, Turkey
Thanks Reach out for Questions and Answers! CAdViSE: Cloud-based Adaptive Video Streaming Evaluation Framework for the Automated Testing of Media Players