Selective Data Compression Using Pattern Analysis in Input Buffers
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Solution Overview
Problem
Conventional data compression technologies lack efficiency in determining whether to compress data, leading to suboptimal storage solutions, as they do not effectively analyze data patterns before compression, resulting in inefficient use of storage space.
Innovation Solution
A data compression method that analyzes data patterns using a data pattern analyzer, which includes a header analyzer and an estimator, to determine whether to compress data based on indication bits, symbol frequencies, and codeword assignments, allowing for selective compression or bypassing of data in an input buffer.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data compression is applied to all data, then storage space efficiency is improved, but processing time and energy consumption increase
Solution Approach 1:
The patent applies preliminary action by analyzing data patterns before compression to determine whether compression is beneficial. The data pattern analyzer examines data characteristics in advance, and only data suitable for compression is processed, avoiding unnecessary compression operations and saving processing time.
Solution Approach 2:
The patent changes the parameter of data by analyzing patterns such as symbol frequencies and data characteristics. Based on these parameter changes, the system determines whether to apply compression, thereby optimizing the balance between storage efficiency and processing time.
2Productivity
If data pattern analysis is performed before compression, then compression efficiency is improved, but device complexity increases
Solution Approach 1:
The patent segments the compression system into distinct functional modules: a data pattern analyzer for analyzing data characteristics, and a compression unit for performing compression. This segmentation allows each module to specialize in its function, improving overall compression efficiency while managing complexity through modular design.
Solution Approach 2:
The data pattern analyzer acts as an intermediary between the data input and the compression unit. It analyzes data patterns and provides guidance to the compression unit, enabling efficient compression decisions without requiring the compression unit itself to be overly complex.
3Speed
If compression is applied without pattern analysis, then processing speed is maintained, but storage space optimization is reduced
Solution Approach 1:
The system performs preliminary pattern analysis on data before compression to identify data suitable for compression. This preliminary action ensures that only data that will benefit from compression is processed, maintaining processing speed by avoiding unnecessary compression while optimizing storage space for suitable data.
Solution Approach 2:
The system changes the approach by introducing pattern analysis parameters such as symbol frequency counts and data characteristic evaluations. These parameter changes enable the system to make informed decisions about compression, optimizing storage space without significantly impacting processing speed.
Data Source
AI summary
A method of operating a data compression device includes analyzing data using an analyzer and generating a result of the analysis, while the data is buffered by an input buffer, and selectively compressing the buffered data according to the result of the analysis. A data compression device includes a data pattern analyzer configured to analyze data transmitted to an input buffer, and generate an analysis code based on the analysis of the data; and a data compression manager configured to selectively compress the data in the input buffer based on the analysis code.