Correlation-Based Data Compression for Reliable High-Volume Transfer
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Solution Overview
Problem
Existing data compression techniques struggle to achieve a desirable compression ratio while maintaining high reliability, especially in distributed systems where large volumes of data need to be efficiently compressed for analysis and security reasons.
Innovation Solution
A data compression system that extracts and verifies correlations within data sets to compress data effectively, using a correlation extraction and verification process to identify reliable correlations for efficient compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If data compression is performed to reduce package size for security and cost reasons, then data transmission efficiency is improved, but data reliability deteriorates
Solution Approach 1:
The patent applies preliminary action by extracting and verifying correlation rules from historical data before actual compression occurs. The system pre-establishes reliable correlation patterns that can be safely used during compression, ensuring that data reliability is maintained while achieving compression. This is evident in the correlation extraction means that analyzes historical data to identify patterns before compression is applied to new data.
Solution Approach 2:
The patent implements feedback through the correlation verification means that continuously validates correlation rules against incoming data. This feedback mechanism ensures that only reliable correlations are used for compression, and allows the system to adapt when correlations change or become invalid. The verification process provides ongoing feedback to maintain data reliability while achieving compression goals.
2Quantity of substance
If existing compression techniques are used to compress large volumes of data, then data volume is reduced, but compression ratio is insufficient
Solution Approach 1:
The patent applies parameter changes by transforming data representation based on extracted correlation patterns. Instead of using fixed compression algorithms, the system dynamically changes data parameters by replacing correlated data elements with references to correlation rules, achieving higher compression ratios. The correlation extraction means identifies patterns that allow more aggressive compression than traditional methods.
Solution Approach 2:
The patent applies segmentation by dividing the compression process into distinct stages: correlation extraction, correlation verification, and actual compression application. This segmentation allows each component to be optimized independently, with the correlation extraction focusing on pattern identification and the compression stage focusing on applying those patterns for maximum ratio achievement.
3Reliability
If correlation-based compression is applied to maintain high reliability, then data reliability is improved, but system complexity increases
Solution Approach 1:
The patent applies the extraction principle by separating the complex correlation analysis function into a dedicated correlation extraction means that operates independently from the main compression process. This extraction of the complex analytical function allows the main compression system to remain relatively simple while still achieving high reliability through the pre-extracted correlation rules.
Solution Approach 2:
The patent reduces system complexity during operation by performing the complex correlation analysis in advance during a preliminary extraction phase. The correlation extraction means analyzes historical data beforehand to establish reliable patterns, so that during actual compression operations, the system only needs to apply pre-verified rules rather than performing complex analysis in real-time.
Data Source
AI summary
The system includes a correlation extraction means for extracting at least one candidate for a correlation from a collected given data set, based on a relationship between units of data in the given data set; a correlation verification means for verifying whether or not the units of data in the given data set satisfy the correlation extracted by the correlation extraction means; and a data compression means for compressing the given data set with use of the correlation, based on the result of verification by the correlation verification means.