Partial-Statistics Data Compression for Lower Buffer and Delay
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Solution Overview
Problem
Current data compression techniques are complex and time-consuming, leading to inefficiencies in storage management, increased hardware costs, and high power consumption due to the need for large compressors and extensive statistical analysis.
Innovation Solution
Implementing a method that uses partial statistics to select data compression algorithms, reducing the size of the buffer needed for compression and allowing for immediate second-level compression, thereby reducing the size and power consumption of data compression hardware.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If full statistics are collected for all symbols before selecting compression algorithms, then compression ratio is optimized, but processing time and device complexity increase significantly
Solution Approach 1:
The patent applies partial statistics by collecting statistical information from only a subset of symbols (e.g., first N symbols or symbols from specific positions) rather than all symbols in the data frame. This partial statistical analysis enables algorithm selection with negligible impact on compression ratio while dramatically reducing processing time and complexity. The buffer memory size is reduced from requiring storage of all symbols to storing only the partial set needed for statistics collection.
2Measurement precision
If large buffer memory is allocated to store all symbols for statistical analysis, then complete statistics can be obtained, but hardware size and power consumption increase
Solution Approach 1:
The patent extracts only the necessary portion of data for statistical analysis by selecting a subset of symbols (partial set) from the complete symbol frame. This extracted partial set is stored in a reduced-size buffer memory, eliminating the need to allocate buffer space for all symbols. The extraction principle directly reduces buffer memory size while maintaining sufficient statistical accuracy for algorithm selection.
3Productivity
If complex multi-level compression algorithms are implemented, then compression efficiency is improved, but device complexity and manufacturing cost increase
Solution Approach 1:
The patent implements dynamic algorithm selection by using collected statistics to choose the most appropriate compression algorithm based on the actual data characteristics. Rather than implementing all possible compression algorithms in hardware, the system dynamically selects from a set of algorithms based on statistical analysis of a partial symbol set. This dynamic approach achieves high compression efficiency while keeping device complexity manageable through selective implementation.
4Measurement precision
If extensive statistical analysis is performed on all data before compression, then optimal compression algorithms are selected, but processing delay increases
Solution Approach 1:
The patent performs preliminary statistical analysis on a partial set of symbols (e.g., first N symbols or initial portion of data frame) to enable early algorithm selection. This preliminary action on a subset of data allows the system to begin compression processing sooner rather than waiting to analyze all symbols. The buffer memory stores only this partial set for preliminary analysis, enabling faster processing while maintaining sufficient accuracy for algorithm selection.
Data Source
AI summary
A data storage device includes at least one data storage medium and a controller that is operably coupled to the at least one data storage medium. The controller receives the bit stream in a data storage device and performs a first level of compression on the received bit stream to obtain a symbol frame including a plurality of symbols. The controller encodes an initial portion of the plurality of symbols contained in the symbol frame by a fixed encoding scheme. The controller also collects statistics for the initial portion of the symbol frame. The controller then selects at least one data compression algorithm based on the collected statistics. The controller then performs compression encoding on a remaining portion of the symbol frame with the selected at least one data compression algorithm.