Moving-Window Codebook Encoding for Low-Latency Media Storage
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Solution Overview
Problem
Cloud-based digital media storage systems face significant challenges in managing encoding latency, which leads to operational inefficiencies and undesirable user experiences due to the need for real-time processing and storage of large digital media files, particularly in applications like DVR services where immediate access and playback are expected.
Innovation Solution
The implementation of a 'moving window' codebook training and encoding approach, where codebooks are trained and employed in real-time as digital assets are received, allowing for immediate encoding and storage with minimal delay, using a bootstrap codebook for initial portions and progressively training new codebooks for subsequent portions, thereby reducing latency and optimizing resource usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If codebook training is performed before encoding the entire digital asset, then encoding quality is improved, but encoding latency increases
Solution Approach 1:
The patent divides the digital asset into multiple portions and trains codebooks incrementally for each portion rather than training a single codebook for the entire asset beforehand. This segmentation allows encoding to begin earlier with available codebooks while continuing to improve quality as more codebooks are trained, thus reducing latency while maintaining encoding quality.
Solution Approach 2:
The patent performs preliminary codebook training on initial portions of the digital asset before the entire asset is received. These pre-trained codebooks are then available to start encoding subsequent portions immediately, eliminating the need to wait for complete asset reception and full codebook training before beginning encoding, thereby reducing encoding latency.
2Manufacturing precision
If the entire digital asset is received before encoding, then complete asset encoding quality is improved, but playback latency increases
Solution Approach 1:
The patent segments the digital asset into multiple portions that can be processed independently. Each portion is encoded with codebooks trained on that specific portion, allowing incremental encoding and storage as portions are received, enabling earlier playback without compromising overall encoding quality.
Solution Approach 2:
The patent maintains continuous encoding operations by training codebooks on received portions and immediately encoding subsequent portions without interruption. This continuous process ensures that encoding quality is maintained throughout while minimizing delays, enabling near real-time playback.
3Loss of time
If codebooks are trained on received portions in real-time, then encoding latency is reduced, but processing resource demands increase
Solution Approach 1:
The patent divides the codebook training process into smaller segments corresponding to different portions of the digital asset. This allows training to occur incrementally on available portions rather than requiring all resources simultaneously for complete asset training, reducing peak processing demands while maintaining low encoding latency.
Solution Approach 2:
The patent performs partial codebook training on initial portions of the digital asset before the entire asset is received, using available data to create functional codebooks. This partial action enables encoding to begin with sufficient quality while distributing processing demands over time rather than concentrating them all at once.
4Quantity of substance
If compression is applied to reduce storage requirements, then storage capacity is optimized, but encoding complexity increases
Solution Approach 1:
The patent applies compression through codebook training on segmented portions of the digital asset rather than attempting to compress the entire asset at once. This segmentation simplifies the encoding process by breaking down the complex task into manageable portions while achieving cumulative compression effects that optimize storage capacity.
Data Source
AI summary
Embodiments of the present disclosure provide systems, methods, and computer storage media for mitigating latencies associated with the encoding of digital assets. Instead of waiting for codebook generation to complete in order to encode a digital asset for storage, embodiments described herein describe a shifting codebook generation and employment technique that significantly mitigates any latencies typically associated with encoding schemes. As a digital asset is received, a single codebook is trained based on each portion of the digital asset, or in some instances along with each portion of other digital assets being received. The single codebook is employed to encode subsequent portion(s) of the digital asset as it is received. The process continues until an end of the digital asset is reached or another command to terminate the encoding process is received. To encode an initial portion of the digital asset, a bootstrap codebook can be employed.