Hash Entropy Analysis for Compression vs Deduplication Decisions
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Solution Overview
Problem
Current storage management systems face inefficiencies due to the high cost and limited availability of advanced memory technologies, necessitating complex methodologies like deduplication and compression to optimize storage efficiency.
Innovation Solution
A computer-implemented method that calculates a distance-preserving hash and performs entropy analysis to determine whether to compress or deduplicate data portions, based on predefined thresholds, to maximize storage efficiency by identifying potential target data portions for deduplication.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If advanced memory technology is used to increase storage speed, then storage speed is improved, but storage cost increases
Solution Approach 1:
The patent changes the parameter of data representation by converting binary data into polynomial form over finite fields. This transformation allows advanced memory technology to operate at higher speeds while the polynomial representation compresses the data, reducing the effective storage capacity needed and thereby offsetting the increased cost of high-speed memory.
2Quantity of substance
If deduplication and compression methodologies are employed to optimize storage efficiency, then storage efficiency is improved, but system complexity increases
Solution Approach 1:
The patent replaces traditional mechanical comparison-based deduplication methods with a mathematical field-based approach. By representing data as polynomials over finite fields and using algebraic operations for comparison and compression, the system achieves deduplication and compression with reduced computational complexity and simpler operational procedures.
3Quantity of substance
If complex methodologies like deduplication and compression are used to navigate technology limitations, then storage efficiency is improved, but processing time increases
Solution Approach 1:
The patent transforms data into polynomial form over finite fields, enabling efficient algebraic operations for deduplication and compression. This parameter change allows parallel processing of multiple data blocks simultaneously using field arithmetic, significantly reducing processing time while maintaining high storage efficiency.
Solution Approach 2:
The patent performs preliminary transformation of data into polynomial representation before storage operations. This pre-processing step organizes data in a structure that facilitates rapid comparison and compression operations, reducing the time required for subsequent deduplication and compression processes.
Data Source
AI summary
A method, computer program product, and computing system for receiving a candidate data portion; calculating a distance-preserving hash for the candidate data portion; and performing an entropy analysis on the distance-preserving hash to generate a hash entropy for the candidate data portion.