Edge Transcoding for ABR Streaming Storage Optimization
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Solution Overview
Problem
Existing media streaming technologies face challenges in reducing storage costs and transcoding complexity while maintaining quality, particularly in adaptive bit-rate (ABR) streaming, due to high storage requirements and inefficiencies in caching and delivery edge optimization.
Innovation Solution
The implementation of just-in-time transcoding using a bottoms-up scalable coded representation and hint streams, which allows for on-demand generation of ABR streams at specific resolutions and bit-rates, reducing storage needs and computational complexity by deriving lower resolution or quality streams from scalable coded layers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If multiple distinct bit streams are cached at the delivery edge to handle device diversity and network conditions, then the quality of experience is improved, but the storage requirements increase significantly (3-4×)
Solution Approach 1:
The patent segments the video content into smaller chunks and creates multiple representations (different resolutions and bitrates) of each chunk. Instead of caching complete separate bit streams, the system segments content and generates multiple versions on-demand, reducing the storage burden while maintaining quality of experience across different device capabilities and network conditions.
Solution Approach 2:
The system dynamically generates appropriate bit stream representations at the delivery edge based on real-time device capabilities, network conditions, and user preferences. This dynamic approach eliminates the need to pre-cache all possible bit stream variants, as representations are created only when needed, significantly reducing storage requirements while maintaining reliability.
2Adaptability or versatility
If packaging formats and content protection schemes are pre-created and stored for all variants, then delivery compatibility is improved, but storage requirements increase (2-3×)
Solution Approach 1:
The system performs preliminary packaging and content protection setup at the source, creating a flexible template structure that can accommodate multiple formats and protection schemes. This preliminary action enables on-demand generation of specific variants without needing to pre-create and store all possible packaging combinations, reducing storage requirements while maintaining delivery compatibility.
Solution Approach 2:
The patent changes the approach from storing fixed packaging variants to dynamically adjusting packaging parameters (formats, protection schemes) based on device capabilities and delivery requirements. This parameter-based approach allows the system to generate appropriate packaging on-demand, eliminating the need to pre-store multiple packaging variants.
3Reliability
If private-copy mode is implemented for cDVR to meet legal requirements, then subscriber-specific access control is improved, but storage requirements increase proportionally with the number of subscribers
Solution Approach 1:
The system implements a universal content protection mechanism that works across all subscribers using shared cryptographic keys and authentication protocols. Instead of creating separate protected copies for each subscriber, the system uses multi-functional protection schemes that provide subscriber-specific access control through centralized authentication, dramatically reducing storage requirements while maintaining legal compliance.
Solution Approach 2:
The patent uses cryptographic copying and authentication mechanisms where a single protected content representation can serve multiple subscribers through secure key management and authentication. This approach allows private-copy mode functionality to be achieved without creating physical separate copies for each subscriber, reducing storage requirements proportionally.
4Quantity of substance
If just-in-time transcoding is implemented to reduce storage needs, then storage costs are reduced, but computational complexity increases
Solution Approach 1:
The system segments video content into smaller chunks that can be independently transcoded and cached. This segmentation allows just-in-time transcoding to be applied to smaller, more manageable units, reducing the computational complexity of each transcoding operation while maintaining the overall storage reduction benefits.
Solution Approach 2:
The patent performs preliminary encoding and preparation of content at the source with multiple representations already created. This preliminary action reduces the computational burden of just-in-time transcoding at the delivery edge, as the system only needs to perform final format conversion and packaging rather than full encoding, balancing storage reduction with computational complexity.
Data Source
AI summary
A system includes an interface unit to receive a request, from a media client, to obtain a segment of media content at an ABR representation, and a transcoding unit. The transcoding unit includes a scalable decoder, hint stream decoder, and re-encoder. The scalable decoder receives and decodes a set of two or more layers of a scalable coded representation corresponding to the requested segment of media content at the requested ABR representation to provide a set of media frames and scalable stream information for the segment. The hint stream decoder receives and decodes a hint stream corresponding to the requested segment of media content at the requested ABR representation and the scalable stream information to provide transcoding hints for the segment. The re-encoder re-encodes the set of media frames using the transcoding hints to provide an encoded bit stream corresponding to the requested segment of media content.