Video Compression System Dynamic Processor Load Control
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Solution Overview
Problem
Video data compression in videoconferencing systems places significant computational demands on processors, potentially leading to maximum utilization and interference with other applications, especially in environments with varying processor capabilities and bandwidth requirements.
Innovation Solution
A method that determines processor performance data and video data acquisition rate to identify optimal compression settings, dynamically adjusting compression levels to maintain processor utilization within set limits, thereby reducing computational demands and ensuring efficient data transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If motion detection and motion vector analysis are performed to reduce bandwidth, then data transmission efficiency is improved, but processor utilization increases to maximum levels
Solution Approach 1:
The system dynamically adjusts compression settings based on real-time processor performance monitoring. The compression level is not fixed but adapts during operation, switching between different compression algorithms and intensity levels to match available processor resources, thereby resolving the contradiction between maintaining high compression and avoiding processor overload
Solution Approach 2:
The system changes compression parameters such as search area size, block size, and algorithm complexity based on processor capacity. When processor utilization is high, parameters are adjusted to reduce computational demand while maintaining acceptable compression ratios, thus balancing transmission efficiency with processor workload
2Loss of information
If detailed motion vector analysis with large search areas is used, then compression ratio is improved, but computational complexity increases
Solution Approach 1:
The system applies different compression strategies to different regions of the video frame based on local characteristics. High-motion regions receive more aggressive compression with larger search areas, while low-motion regions use simpler algorithms, optimizing the balance between compression ratio and computational complexity locally rather than uniformly across the entire frame
Solution Approach 2:
The system performs partial motion analysis by limiting the search area size and block processing granularity. Instead of analyzing every pixel or large blocks uniformly, it selectively applies motion detection to regions where it provides the most benefit, reducing overall computational complexity while maintaining acceptable compression performance
3Quantity of substance
If high compression settings are applied to reduce bandwidth requirements, then network bandwidth consumption is reduced, but processor resources are excessively consumed
Solution Approach 1:
The system implements feedback control by continuously monitoring processor utilization and adjusting compression settings accordingly. When processor resources are heavily consumed, the system reduces compression intensity to free up resources, and when resources are available, it increases compression to reduce bandwidth usage, creating a self-regulating system that balances both objectives
Solution Approach 2:
The system performs preliminary assessment of processor capacity and available bandwidth requirements before initiating compression. Based on this preliminary analysis, it pre-configures appropriate compression settings that are expected to meet bandwidth targets without overloading the processor, avoiding the need for extreme compression that would consume excessive resources
Data Source
AI summary
A method for selecting a compression setting to use during a communications session to compress streaming video data includes the steps of determining processor performance data for at least one processor, determining a video data acquisition rate, and using the processor performance data and the acquisition rate to identify a compression setting for the data communications session.