Warm-Start File Compression Using Sequence Alignment Matrices
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Solution Overview
Problem
Existing data compression methods are inefficient in reducing storage and bandwidth requirements, particularly for large files, and often require significant computational resources.
Innovation Solution
A compression engine that utilizes multiple sequence alignment to split files into aligned sequences, generate a consensus sequence, and represent the original file as a list of pointer pairs, allowing for efficient compression and decompression.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional compression methods are used, then compression is achieved, but computational resources and time are excessively consumed
Solution Approach 1:
The patent applies preliminary action by performing a warm start compression on a first file to generate a compression matrix before compressing the second file. This pre-computed matrix serves as a foundation for subsequent compressions, eliminating the need to perform the same computationally intensive alignment operations repeatedly. The warm start compression establishes sequence alignments and generates a reusable compression matrix that accelerates future compression operations on similar files.
Solution Approach 2:
The patent utilizes copying by reusing the compression matrix generated from the first file when compressing the second file. Instead of performing independent compression operations, the system copies the structural framework and alignment information from the first compression to the second, significantly reducing computational overhead. The compression matrix acts as a template that can be applied to multiple files with similar characteristics.
2Quantity of substance
If compression ratio is increased, then storage space is reduced, but computational complexity increases
Solution Approach 1:
The patent applies segmentation by dividing files into multiple sequences or blocks that can be independently aligned and compressed. The compression matrix organizes data into discrete sequence segments that can be processed separately. This segmentation allows the system to achieve high compression ratios by identifying and exploiting redundancies within each segment while keeping the computational complexity of each individual segment manageable.
Solution Approach 2:
The warm start compression performs preliminary alignment and matrix generation operations once, creating a reusable structure that enables subsequent compressions to achieve high ratios without repeating the full computational process. The pre-computed compression matrix captures the essential alignment information needed for high-ratio compression, allowing future operations to focus only on applying the established patterns rather than rediscovering them.
Data Source
AI summary
Compressing files is disclosed. An input file to be compressed is first aligned. Aligning the file includes splitting the file into sequences that can be aligned. The result is a compression matrix, where each row of the matrix corresponds to part of the file. The compression matrix may also serve as a warm start if additional compression is desired. Compression may be performed in stages, where an initial compression matrix is generated in a first stage using larger letter sizes for alignment and then a second compression stage is performed using smaller letter sizes. A consensus sequence id determined from the compression matrix. Using the consensus sequence, pointer pairs are generated. Each pointer pair identifies a subsequence of the consensus matrix. The compressed file includes the pointer pairs and the consensus sequence.