Compression Engine Sequential Data Stream Optimization
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Solution Overview
Problem
Conventional data compression techniques fail to effectively reduce storage space for highly disordered or naturally originated data, such as images and videos, due to inefficient prediction models and file storage blocking issues, leading to wasted time and energy in compression and decompression processes without significant storage size reduction.
Innovation Solution
The approach involves identifying and grouping sequentially efficiently compressible data sequences, transforming data to increase orderliness, and packing similar data streams together to maintain a consistent prediction model, thereby optimizing compression efficiency and overcoming file storage blocking limitations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If conventional compression algorithms are applied to highly disordered data, then compression time is consumed, but storage size reduction is not achieved
Solution Approach 1:
The patent applies preliminary actions by pre-processing data to identify highly disordered sequences before compression. The system detects patterns of disorderliness and marks these sequences for special handling, transforming the data state before the actual compression process begins. This preliminary identification prevents wasted compression operations on data that cannot be compressed, thereby resolving the contradiction between consuming compression time and achieving storage reduction.
2Quantity of substance
If compression is performed on all data, then processing time is spent, but energy is wasted on data that cannot be compressed
Solution Approach 1:
The system implements self-service by enabling data to indicate its own compressibility characteristics. Through embedded metadata and self-diagnosis mechanisms, data sequences automatically provide information about their disorderliness and compression potential. This allows the compression system to make informed decisions without external analysis, eliminating energy waste by only compressing data that can actually be reduced in size.
3Ease of manufacture
If file storage blocking is used, then storage organization is simplified, but actual storage reduction is prevented due to fixed block sizes
Solution Approach 1:
The patent applies segmentation by dividing files into variable-sized segments based on compressibility characteristics rather than using fixed block sizes. Highly compressible segments are stored in compressed form, while highly disordered segments are stored uncompressed or with minimal compression. This segmentation strategy maintains storage organization simplicity while achieving actual storage reduction by adapting block sizes to the actual compression potential of each data segment.
Data Source
AI summary
Prediction-based compression engines are spoon-fed with sequentially efficiently compressible (SEC) streams of input data that make it possible for the compression engines to more efficiently compress or otherwise compact the incoming data than would be possible with streams of input data accepted on a TV-raster scan basis. Various techniques are disclosed for intentionally forming SEC input data streams. Among these are the tight packing of alike files or fragments into concatenation suitcases and the decomposition of files into substantially predictably consistent (SPC) fragments or segments that are routed to different suitcases according to their type. In a graphics-directed embodiment, image frames are partitioned into segment areas that are internally SPC and multidirectional walks (i.e., U-turning walks) are defined in the segment areas where these defined walks are traced during compression and also during decompression. A variety of pre-compression data transformation methods are disclosed for causing apparently random data sequences to appear more compressibly alike to each other. The methods are usable in systems that permit substantially longer times for data compaction operations than for data decompaction operations.