Dynamic Computational Resource Allocation for Video Encoding
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Solution Overview
Problem
Current video encoder implementations face challenges in dynamically managing computational resources to balance video quality and bitrate, particularly in real-time or near real-time encoding of multimedia content streams, especially in dynamic distribution modes where audience measurement and video content complexity vary.
Innovation Solution
A computer-implemented method that uses a mixed criterion combining audience measurement and video content complexity to dynamically allocate computational resources, allowing for refined resource management and improved encoding performance by adjusting resources based on audience demand and content complexity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If computational resources are increased to improve video quality, then video quality improves, but resource consumption increases
Solution Approach 1:
The system dynamically adjusts computational resource allocation based on real-time conditions. The resource allocation criterion changes over time according to audience measurement and video complexity variations, allowing the encoder to adapt resource usage to actual needs rather than using fixed allocation
Solution Approach 2:
The system changes the parameter of computational resource allocation by introducing a dynamic criterion that combines audience measurement and video complexity. This criterion modifies resource allocation parameters based on varying conditions, optimizing the balance between video quality and resource consumption
2Use of energy by moving object
If computational resources are decreased to reduce resource consumption, then resource consumption decreases, but video quality deteriorates
Solution Approach 1:
The system dynamically adjusts the resource allocation parameter based on the computed criterion combining audience measurement and video complexity. When resources need to be decreased, the system identifies segments where quality reduction is least impactful, maintaining acceptable quality while reducing consumption
Solution Approach 2:
The system provides dynamic adjustment capability, allowing computational resources to be decreased during low-complexity segments or periods with lower audience demand, while maintaining higher resources during critical segments, thus optimizing the quality-consumption tradeoff
3Productivity
If resource allocation is based only on video complexity, then encoding efficiency improves, but adaptability to audience demand decreases
Solution Approach 1:
The system merges two previously separate criteria: video complexity and audience measurement. By combining these criteria into a unified resource allocation criterion, the system simultaneously achieves encoding efficiency (from complexity analysis) and adaptability to audience demand (from audience measurement)
Solution Approach 2:
The unified resource allocation criterion serves multiple functions: it maintains encoding efficiency through complexity analysis while simultaneously providing adaptability to audience demand. This multi-functional criterion replaces the need for separate allocation mechanisms
4Adaptability or versatility
If resource allocation is based only on audience measurement, then adaptability to audience demand improves, but encoding efficiency decreases
Solution Approach 1:
The system combines audience measurement with video complexity analysis in the unified criterion. This ensures that resource allocation is adapted to audience demand while maintaining encoding efficiency through the complexity component, preventing resource waste on already-simple segments
5Ease of operation
If fixed computational resources are allocated to all channels, then resource management simplicity improves, but resource allocation optimization decreases
Solution Approach 1:
The system transitions from fixed to dynamic resource allocation. The resource allocation criterion is computed dynamically for each channel based on its specific audience measurement and video complexity characteristics, optimizing resource distribution while maintaining manageable complexity through automated computation
Data Source
AI summary
A method for managing computational resources allocated for encoding of one or more multimedia content streams for distribution in dynamic mode to viewing devices through a distribution network is proposed, which comprises, by a processing node of the distribution network: obtain, for a multimedia content stream corresponding to a channel distributed to the viewing devices, a value of a computational resource allocation criterion, wherein the computational resource allocation criterion comprises an audience measurement for the corresponding channel and a video content complexity of the multimedia content stream; and determine, based on the computational resource allocation criterion, an allocation of computational resources of a computing platform configured for encoding the multimedia content stream.