Improving On-scale Video Streaming with Audience-Aware Streaming
Live linear streams are typically produced using a fixed bitrate ladder and codec mix. This approach locks in storage, computing, delivery costs, and power consumption. Unpopular channels have the same operating costs as popular ones. Content distributors would much rather focus their resources on popular content and maximize aggregate Quality of Experience (QoE) while minimizing storage, computing, delivery, and power. This paper describes a collaboration between Ateme (a provider of video compression and delivery solutions) and Akamai (a global compute and delivery provider) in which such optimization is achieved. Player viewing sessions are collected by Akamai using the Common Media Client Data (CMCD) standard and fed in a real-time data feed to an Ateme stream optimizer. The optimizer gathers data on the viewership count, geodiversity, device diversity, and device capability and then dynamically adjusts the cloud compute resources allocated to the stream, varying the bitrate ladder and codec mix offered to provide the best quality to the popular streams while minimizing delivery costs and power consumption. The paper describes the proof-of-concept system that was built. It presents the real-world results that were obtained to validate the hy-pothesis that live linear Over-The-Top (OTT) operations can be optimized with the addition of real-time audience data.
- Print ISSN
- 1545-0279
- Electronic ISSN
- 2160-2492
- Published
- 2025-01
- Content type
- Original Research
- Keywords
- common media common data, content delivery network, video end to end optimization, audience aware
- DOI
- 10.5594/JMI.2025/CVFK2383