Storage Compression Selection for Faster Data Decompression
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Solution Overview
Problem
Existing data compression techniques in storage systems fail to effectively balance compression and decompression rates, leading to suboptimal read performance due to inadequate consideration of decompression time and overhead in algorithm selection, particularly when dealing with varying data types and historical prediction inaccuracies.
Innovation Solution
A data compression system that employs multiple compression algorithms, dynamically selecting between them based on current compression rates and decompression times to optimize read performance by prioritizing algorithms with better compression rates while minimizing decompression time, thereby reducing the overall read performance impact.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If a compression algorithm with high compression rate is selected, then storage capacity efficiency is improved, but decompression time increases and read performance deteriorates
Solution Approach 1:
The patent implements dynamic algorithm selection that adapts to current system conditions. The storage system monitors decompression time metrics and selectively applies different compression algorithms based on real-time performance requirements, transitioning from static to dynamic decision-making to balance compression efficiency with read performance
Solution Approach 2:
The system changes the parameter of algorithm selection by evaluating decompression time as a key metric. By adjusting which algorithm is applied based on decompression performance thresholds, the system optimizes the balance between compression rate and read performance, treating decompression time as a controllable parameter
2Productivity
If multiple compression algorithms are evaluated and selected based on compression rate, then compression efficiency is improved, but calculation overhead and device complexity increase
Solution Approach 1:
The patent extracts the essential selection criterion to decompression time alone, removing unnecessary complexity from the algorithm selection process. By focusing on this single key metric rather than evaluating multiple parameters simultaneously, the system simplifies the decision-making mechanism while maintaining compression efficiency
Solution Approach 2:
The storage system performs self-evaluation by monitoring its own decompression time metrics and automatically selecting appropriate algorithms without external intervention. This self-service mechanism reduces the need for complex external control systems while maintaining optimal performance
3Adaptability or versatility
If compression algorithm is selected based on past history prediction, then adaptability is improved, but prediction accuracy deteriorates when current data differs from historical patterns
Solution Approach 1:
The patent implements a feedback mechanism where the system continuously monitors actual decompression time performance and uses this real-time information to adjust algorithm selection. This feedback loop allows the system to adapt to current data characteristics rather than relying solely on historical predictions, improving measurement precision
Solution Approach 2:
The system transitions from static historical prediction to dynamic real-time evaluation by monitoring current decompression performance. This dynamic approach allows the system to adapt to changing data patterns while maintaining accurate performance measurement through continuous monitoring
Data Source
AI summary
A data compression system in a storage system compresses data with a first compression method to generate compressed data, determines whether a compression rate of the compressed data is better than a predetermined reference, outputs data obtained by compressing the data by the compression method having a better compression rate than that of the other compression method of the first compression method and a second compression method when it is determined that the compression rate is better than the reference, and outputs data obtained by compressing the data by the compression method having a worse compression rate than that of the other compression method of the first compression method and the second compression method when it is determined that the compression rate is equal to or worse than the reference.