Dynamic Codec Adaptation for Distributed Video Processing
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Solution Overview
Problem
In distributed real-time processing of video data in network-centric data centers, the high volume of data exchanged between processing nodes leads to network congestion, making it difficult to efficiently distribute application components across different nodes while minimizing computing effort and network usage.
Innovation Solution
A dynamic configurable coding and representation format is implemented between processing components, automatically configured based on the knowledge of subsequent processing functions, allowing for optimized media compression by selecting appropriate codecs and data representations that preserve only the necessary information, reducing data transmission over network links.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If data is transmitted in uncompressed format between processing nodes, then processing quality is maintained, but network bandwidth consumption increases
Solution Approach 1:
The patent dynamically changes compression parameters (codec type, compression level, resolution) based on the specific requirements of receiving components. Different processing components receive data with different compression levels - components needing high precision get less compressed data, while others receive highly compressed data, thus optimizing the trade-off between processing quality and bandwidth consumption.
Solution Approach 2:
The system applies different data representation qualities to different receiving components based on their specific processing needs. Each component receives data optimized for its function - for example, components performing detailed analysis receive higher quality data while components performing coarse processing receive lower quality data, thereby reducing overall network bandwidth consumption while maintaining necessary processing quality.
2Quantity of substance
If compression is applied to reduce network traffic, then bandwidth usage decreases, but processing time increases
Solution Approach 1:
The system performs compression and data representation transformation in advance, before data transmission begins. By pre-processing data into optimized representations tailored to each receiving component's needs, the system reduces the computational burden during real-time processing, thereby minimizing processing time delays while still achieving significant bandwidth reduction.
Solution Approach 2:
The patent implements dynamic adaptation of compression and representation formats based on real-time conditions including component requirements, data characteristics, and system state. This dynamic approach allows the system to optimize the balance between compression ratio and processing speed for each transmission, preventing excessive processing time while maximizing bandwidth efficiency.
3Adaptability or versatility
If generic compression formats are used, then compatibility is improved, but processing efficiency decreases
Solution Approach 1:
The system dynamically selects and configures compression parameters including codec type, bit depth, resolution, and compression level based on the specific requirements of each receiving processing component. This parameter adaptation allows the system to use highly efficient, specialized compression formats for each component rather than generic formats, significantly improving processing efficiency while maintaining compatibility through standardized interfaces.
Solution Approach 2:
The patent applies specialized compression and representation formats tailored to each receiving component's processing needs. Instead of using a single generic format for all components, the system optimizes the data representation for each component's specific algorithm and requirements, thereby maximizing processing efficiency for each component while maintaining system-wide compatibility through the adaptive framework.
4Productivity
If processing components are distributed across multiple nodes, then resource utilization is optimized, but network complexity increases
Solution Approach 1:
The patent implements a universal adaptive compression and data representation framework that works across all processing nodes and component types. This unified approach handles diverse processing requirements through a single standardized mechanism, reducing network complexity by eliminating the need for multiple specialized protocols while still enabling optimized resource utilization across distributed nodes.
Data Source
AI summary
The present document describes a system comprising at least two processing nodes (1) that are connected by a network, and an application distribution function, which automatically distributes processing components (3) of an application to be run on the system over the nodes (1). The system is configured, when a sending processing component and a corresponding receiving processing component are arranged on different nodes, to determine, based on information about the processing component (3) which receive the data, in which representation to send the data via the corresponding communication channel (4).