Adaptive Video Bitrate Selection Using Client Capacity Feedback
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Solution Overview
Problem
Existing streaming video encoding settings are infrequently updated and do not account for individual viewer capacities, leading to suboptimal viewing experiences due to mismatched bitrates.
Innovation Solution
A feedback loop system that dynamically adjusts encoding bitrates based on real-time client performance data, allowing for optimized bitrate selection tailored to individual viewer capacities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If bitrates are determined based on industry-standard streaming capacities, then encoding is simplified and consistent, but the bitrates do not reflect increases in streaming capacity due to developing technology or specific viewer capacities
Solution Approach 1:
The system implements a feedback mechanism where client performance data (buffering events, playback quality metrics) is collected from viewers and used to automatically adjust encoding bitrates. This closed-loop feedback enables the system to adapt to both technological advances in streaming capacity and individual viewer capabilities without manual intervention, resolving the contradiction between adaptability and complexity.
Solution Approach 2:
The patent transforms static, industry-standard bitrate selection into a dynamic system that continuously evolves based on real-world performance data. Bitrates are no longer fixed but are continuously optimized based on aggregated client performance metrics, allowing the system to adapt to developing technology and specific viewer capacities while maintaining operational simplicity through automated adjustment.
2Reliability
If bitrates are updated frequently based on viewer feedback, then viewing experience is optimized, but system complexity and processing requirements increase
Solution Approach 1:
The system merges data from multiple viewers into aggregated performance metrics, processing information collectively rather than individually for each client. This consolidation reduces processing complexity while maintaining reliable viewing experiences, as the system optimizes bitrates based on population-level patterns rather than requiring complex real-time adjustments for each individual viewer.
Solution Approach 2:
The system updates bitrates based on significant performance thresholds rather than continuously adjusting for every minor variation in viewer experience. By triggering optimizations only when performance metrics cross defined thresholds, the system maintains high viewing quality while avoiding excessive processing complexity associated with continuous fine-tuning.
3Adaptability or versatility
If multiple video streams are encoded at different bitrates, then viewer selection flexibility is improved, but encoding time and computational resources increase
Solution Approach 1:
The system performs preliminary encoding at multiple bitrates based on projected performance needs rather than waiting for performance degradation to occur. By proactively creating multiple encoded versions in advance based on anticipated viewer capacities and performance thresholds, the system provides bitrate selection flexibility while optimizing encoding efficiency through planned, batch processing rather than reactive, individual adjustments.
Data Source
AI summary
A method including encoding a video program into a plurality of video streams, each of the plurality of video streams being encoded at a corresponding one of a plurality of bitrates; providing, to a plurality of viewing clients, an option to select one of the plurality of video streams; determining a streaming capacity of each of the viewing clients; and determining an improved plurality of bitrates based on streaming capacities of the plurality of viewing clients.