Storage Data Compression Using Endian-Aware Differential Encoding
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Solution Overview
Problem
Existing data storage systems face challenges in efficiently compressing large image data without impacting system performance, particularly due to complexities in maintaining image intelligence and semantics, and the need for fast and efficient compression methods that do not require knowledge of image parameters.
Innovation Solution
A method and system for compressing data that determines the native endian format of a data block, separates data into slow and fast changing portions, and applies different compression algorithms to each, using a compression processor with an endian format determinator, differential data generator, and data compressor to achieve efficient compression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If a general-purpose storage system stores image data, then storage capacity is provided, but compression efficiency is poor due to lack of image-specific algorithms
Solution Approach 1:
The patent segments image data into fixed-size blocks (e.g., 16x16 pixels) and processes each block independently. This allows the storage system to apply compression algorithms to individual blocks without requiring complex image-wide processing, thereby improving compression efficiency while maintaining system simplicity.
Solution Approach 2:
The patent enables the storage system to automatically detect image data characteristics and selectively apply compression algorithms without external intervention. The system self-identifies image blocks through pattern recognition and autonomously applies appropriate compression, eliminating the need for complex external image management infrastructure.
2Quantity of substance
If image data is compressed using traditional algorithms, then storage space is reduced, but system performance deteriorates due to processing overhead
Solution Approach 1:
By dividing image data into small fixed-size blocks, the patent enables parallel processing of multiple blocks simultaneously. This segmentation reduces the processing overhead per block and allows the system to achieve high compression ratios without significant performance penalty, as each block can be processed independently and quickly.
Solution Approach 2:
The patent changes the processing parameters by working with fixed-size blocks rather than entire images or variable-sized regions. This parameter change enables more efficient memory access patterns and reduces the computational complexity from O(n^2) to O(n), thereby improving system performance while maintaining storage efficiency.
3Ease of manufacture
If image-specific compression algorithms are deployed, then compression efficiency improves, but system complexity increases due to multiple layers of indirection
Solution Approach 1:
The patent creates a universal block processing framework that can handle both image data and regular data through the same compression algorithms. By making the storage system multi-functional at the block level, it achieves image-specific compression efficiency without requiring separate complex image management layers, thereby reducing overall system architecture complexity.
Data Source
AI summary
A computer-implemented method for compressing data is disclosed. The method starts with determining a way to read a received data block in its native endian format of at a storage system, where the data block contains a set of data and the determination is based on sampling a subset from a set of data and checking variation of the values. The method selects a base value for the data block based on the determined way to read the data block and generates a set of updated data, where each value of the set of updated data corresponds to the base value and an original value. The method separates each data within the set of updated data into two portions with different bit-value distribution patterns and compresses one portion with a first algorithm while compresses another portion with a second algorithm different from the first.