Constant-Slope Bitrate Allocation Across Distributed Video Chunks
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Solution Overview
Problem
Conventional distributed encoding techniques struggle to optimize bitrate allocation across video chunks, leading to sub-optimal tradeoffs between bitrate and visual quality due to lack of feedback between compute instances, resulting in uneven resource allocation and overall visual quality.
Innovation Solution
Implement a constant-slope bitrate allocator using Lagrangian optimization to determine a global bitrate-quality tradeoff, computing a chunk-specific bitrate for each chunk to ensure optimal allocation of bits, thereby optimizing the overall visual quality of the aggregate encode.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single bitrate is computed based on average complexity of source data, then encoding time is optimized through parallel processing, but the visual quality becomes sub-optimal when complexity varies noticeably between source chunks
Solution Approach 1:
The patent applies local quality by computing separate bitrates for different source chunks based on their individual complexity characteristics. Instead of using a single average bitrate for all chunks, the system analyzes each chunk's complexity and allocates bits locally optimized for that specific chunk, thereby maintaining high visual quality in complex regions while efficiently encoding simpler regions.
Solution Approach 2:
The patent implements preliminary action by pre-computing complexity metrics for each source chunk before the actual encoding process. This allows the system to determine optimal bitrates for each chunk in advance, enabling parallel encoding to proceed efficiently while already having the bitrate allocation strategy prepared, thus avoiding quality issues during encoding.
2Manufacturing precision
If constant rate factor encoding is used to improve visual quality uniformity across chunks, then bitrate-quality tradeoff is optimized locally, but globally optimized bitrate allocation is not achieved due to independent compute instance operation
Solution Approach 1:
The patent implements feedback by having the central controller receive complexity information from compute instances and use this feedback to compute globally optimized bitrates. The system collects data from distributed compute instances about their processing status and complexity metrics, then uses this feedback to adjust and allocate bitrates optimally across all chunks, achieving both local quality and global optimization.
Solution Approach 2:
The patent introduces an intermediary central controller that mediates between the distributed compute instances and the bitrate allocation process. This intermediary collects complexity information from compute instances, performs global optimization calculations, and distributes optimized bitrate parameters back to the compute instances, thereby enabling global optimization without requiring direct complex interactions between compute instances.
3Productivity
If per-chunk independent encoding is performed to optimize encoding time, then parallel processing efficiency is improved, but feedback between compute instances is lost making global optimization difficult
Solution Approach 1:
The patent uses an intermediary central controller to preserve feedback information that would otherwise be lost in independent parallel encoding. The compute instances send their complexity metrics and encoding status to the central controller, which maintains this information and uses it for global bitrate optimization, thereby preserving the necessary feedback loop while maintaining parallel processing efficiency.
Solution Approach 2:
The patent establishes a feedback mechanism where compute instances report their processing status and complexity information to the central controller. This feedback allows the system to perform global optimization of bitrate allocation while maintaining the benefits of independent parallel encoding, as the central controller uses the received feedback to make informed bitrate allocation decisions.
Data Source
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AI summary
In one embodiment of the present invention, a bitrate allocation engine allocates bitrates for distributed encoding of source data. Upon receiving a chunk of source data, the bitrate allocation engine generates a curve based on multiple points that each specify a different visual quality level and corresponding encoding bitrate for encoding the chunk. Subsequently, the bitrate allocation engine computes an optimized encoding bitrate based on the generated curve and an optimization factor that is associated with different visual quality levels and corresponding encoding bitrates for multiple chunks of the source data. The bitrate allocation engine then causes the chunk to be encoded at the optimized encoding bitrate. Advantageously, the resulting encoded chunk is optimized with respect to the optimization factor for multiple chunks of the source data.