Product Rendering Controller for Dynamic VOD Asset Conversion
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Solution Overview
Problem
Subscription-based video content service providers face challenges in efficiently managing the conversion of diverse source assets into personalized video streams that conform to prescribed protocols, especially when dealing with dynamic web content and a vast array of Internet-based sources.
Innovation Solution
A product rendering controller (PRC) is employed to manage the process of converting source assets from native formats to video transport streams. The PRC selects the appropriate video product generator pool based on asset attributes and pool characteristics, ensuring efficient processing and transcoding to create personalized VOD products.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the headend decodes and renders each frame of video content to form composite bitmap images, then the web page can be composited together, but the processing time and computational resources increase significantly
Solution Approach 1:
The system performs preliminary actions by pre-processing video content into reusable components and templates before runtime. Video frames are pre-decoded and stored as reusable elements, and web page layouts are pre-configured as templates with placeholder elements. This eliminates the need to decode and compose entire frames at runtime, significantly reducing processing time while maintaining adaptability for dynamic content delivery.
Solution Approach 2:
The system segments video content and web page elements into independent, reusable components. Video frames are divided into discrete elements that can be individually managed and recombined. Web pages are segmented into templates and content placeholders, allowing selective rendering of only necessary portions rather than complete frame-by-frame composition, thereby reducing computational overhead.
2Adaptability or versatility
If the system processes a vast array of Internet-based content sources and converts them to standardized video transport streams, then content versatility increases, but the device complexity and processing overhead increase
Solution Approach 1:
The system implements a universal processing architecture with standardized input/output interfaces that can handle multiple content sources and formats. The template-based rendering engine serves multiple functions by adapting to different content types through configuration rather than requiring separate processing paths. This multi-functional design reduces device complexity while maintaining broad content compatibility.
Solution Approach 2:
The system manages complexity by changing parameters such as resolution, bitrate, and format through configurable processing stages rather than requiring fundamentally different processing paths for each content type. The standardized transport stream format allows flexible parameter adjustment to accommodate diverse source materials without increasing structural complexity of the conversion system.
3Ease of operation
If the headend retrieves and decodes encoded content for each web page request, then personalized content delivery is enabled, but the processing load and resource consumption increase
Solution Approach 1:
The system performs preliminary actions by pre-processing video content into reusable components and caching decoded elements before runtime requests. Video frames are pre-decoded and stored as reusable elements that can be quickly assembled for personalized delivery without repeating the energy-intensive decoding process for each request, significantly reducing energy consumption while maintaining personalization capability.
Solution Approach 2:
The system creates and uses copies of decoded video elements and templates that can be reused across multiple requests. Instead of decoding original encoded content repeatedly for each personalized request, the system copies and recombines pre-decoded elements according to user-specific templates, reducing energy consumption while enabling personalized content delivery.
Data Source
AI summary
A product rendering controller (PRC) manages the overall process of creating video-on-demand (VOD) assets or products from source assets that are obtained from a wide variety of different content sources (e.g., web-based sources) and which are in a wide variety of different native media formats. The source assets are converted to video transport streams such as an MPEG transport stream and transcoded as necessary to create the VOD products. The PRC determines the VOD products that need to be generated, pre-caches data that is to be incorporated into VOD products, and selects the pool of video product generators that is to be used to convert the source assets to VOD products.