Live Stream Parameter Optimization via Pre-Streaming Test
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Solution Overview
Problem
Live stream quality issues due to unforeseen network conditions often require stopping and restarting the stream, which is inconvenient for viewers, especially when stream publishers lack knowledge on adjusting parameters to improve viewing conditions.
Innovation Solution
A pre-streaming test using a second live stream sent to a test audience based on historical data to determine optimal parameters such as frame rate, bit rate, and transcoder type, reducing the need for mid-stream adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If live stream parameters are adjusted to compensate for network conditions, then viewing quality is improved, but the stream must be stopped and restarted which causes inconvenience
Solution Approach 1:
The system performs preliminary testing by sending a test stream to test audience members before the actual live stream begins. This preliminary action allows the system to determine optimal stream parameters (frame rate, bit rate, frame size, transcoder type) in advance, so that when the actual stream starts, these pre-determined parameters can be used immediately without needing to stop and restart the stream for adjustments.
2Reliability
If stream parameters are optimized for viewing quality, then viewer experience is improved, but the complexity of parameter selection increases
Solution Approach 1:
The system automatically determines optimal stream parameters by analyzing test stream performance data collected from test audience members. This self-service approach eliminates the need for publishers to manually configure complex parameters, as the system autonomously selects the optimal frame rate, bit rate, frame size, and transcoder type based on actual network conditions and viewer device characteristics.
Solution Approach 2:
The system dynamically determines stream parameters (frame rate, bit rate, frame size, transcoder type) based on empirical data collected during test stream playback. By changing parameters based on actual measured performance rather than static configurations, the system optimizes viewing quality while removing the complexity of manual parameter selection from the publisher.
3Measurement precision
If a test stream is sent to determine optimal parameters, then stream initialization accuracy is improved, but additional time and resources are required
Solution Approach 1:
The system sends the test stream to a selective subset of audience members (test audience members) rather than all potential viewers. This partial action approach provides sufficient data to determine optimal parameters without requiring excessive time and resources that would be needed to test with the entire audience, thus balancing measurement precision with time efficiency.
Data Source
AI summary
A method includes providing to a media device, prior to streaming of a first live stream, an indication of a test of the first live stream. The indication initiates streaming of a second live stream from the media device to a test audience, and the test audience is based on one or more of an estimated number of viewers of the first live stream, an estimated plurality of locations of the viewers, or an estimated join rate associated with the viewers. The method further includes receiving quality of service (QoS) data associated with the second live stream. The method further includes providing to the media device, based on the QoS data, a message indicating one or more live stream parameters to use during streaming of the first live stream.