Adaptive Compression Mode Switching for Network Data Transfer
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Solution Overview
Problem
Current compression methods for data transmission over networks are inefficient, leading to slow data transfer speeds and high system resource usage, as they do not adapt optimally to changing system loads and compression results.
Innovation Solution
A system and method that dynamically selects and switches between different compression modes based on system load and observed compression results, using a buffer to manage data compression, allowing for identity compression mode when necessary to maintain optimal resource usage and speed.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a specific compression mode is used, then compression ratio is improved, but data transfer speed deteriorates
Solution Approach 1:
The system dynamically switches between different compression modes (e.g., gzip-1 through gzip-9) based on real-time system load conditions and observed compression results, rather than using a fixed compression mode. This allows the system to adaptively balance compression ratio and data transfer speed according to current operational context.
Solution Approach 2:
The system changes compression parameters (specifically the compression level parameter from 1 to 9) based on system load and performance observations. When system load is low or compression results are favorable, higher compression levels are used; when load is high or performance degrades, lower compression levels or identity mode are selected.
2Quantity of substance
If compression is performed, then data size is reduced, but system resource usage increases
Solution Approach 1:
The system monitors system load and compression results in real-time, using this feedback to dynamically adjust compression mode selection. When system resources are constrained or compression performance is poor, the system reduces compression intensity or switches to identity mode, thereby conserving system resources while maintaining acceptable data transfer efficiency.
Solution Approach 2:
The system applies compression selectively rather than uniformly - using full compression only when conditions are favorable, and reducing or eliminating compression (identity mode) when system resources are limited or compression yields poor results. This partial application of compression optimizes the balance between data size reduction and resource consumption.
3Productivity
If compression mode is changed frequently, then optimization is improved, but system complexity increases
Solution Approach 1:
The system segments the compression process into distinct modes (identity mode and multiple gzip levels) that can be independently selected based on system conditions. This segmentation allows for manageable complexity while maintaining the ability to switch between different compression strategies without requiring a completely complex adaptive algorithm.
Data Source
AI summary
A method, system, and apparatus are directed towards compression of content. A portion of content may be compressed using a compression mode. One or more criteria may be evaluated. Based on the evaluated criteria, a decision is made as to whether to select a different compression mode. If selected, the different compression mode may be used to compress another portion of the content. Additional compression modes may be selected and used to compress the content.