Content Delivery Network Transcoding for Encoding Time Reduction
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Solution Overview
Problem
Current content delivery networks (CDNs) inadequately address the delivery of bandwidth-intense content to diverse client devices with varying capabilities and protocols, leading to inefficient content delivery and repeated on-the-fly encoding.
Innovation Solution
The system opportunistically transcodes requested content streams into multiple formats and bit rates based on client device capabilities and business rules, proactively storing content in local libraries to avoid repeated encoding and improve delivery efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If content is delivered on-the-fly without pre-staging, then storage space is conserved, but encoding time and processing load increase
Solution Approach 1:
The system performs preliminary action by proactively transcoding and storing content in multiple formats at origin servers before client requests arrive. When content is requested, the system checks whether pre-transcoded versions exist in local libraries, eliminating the need for real-time transcoding and reducing encoding time significantly.
2Speed
If content is pre-staged in multiple formats, then delivery speed improves, but storage requirements increase
Solution Approach 1:
The system applies local quality by distributing pre-transcoded content selectively to local libraries based on client device characteristics and content access patterns. Different formats are cached at different locations based on local demand, ensuring fast delivery to specific client types while optimizing overall storage utilization across the CDN infrastructure.
3Productivity
If on-the-fly encoding is performed, then storage efficiency is maintained, but processing complexity increases
Solution Approach 1:
The system extracts the complex transcoding operation from the content delivery path by performing it proactively at origin servers. The heavy processing of converting content to multiple formats is removed from the request-response cycle and executed in advance, simplifying the core delivery mechanism while maintaining storage efficiency through intelligent caching strategies.
4Speed
If content is cached locally, then access speed improves, but cache validation complexity increases
Solution Approach 1:
The system implements feedback mechanisms where client device characteristics and content access patterns are continuously monitored. This feedback informs the proactive transcoding decisions, allowing the system to adaptively determine which formats to pre-cache for different client types, optimizing cache utilization while maintaining simple validation through structured cache metadata.
Data Source
AI summary
A system, method and apparatus for opportunistically transcoding requested content streams into one or more formats to provision thereby one or more content storage libraries.