Genomic Data Compression Using BWT and Frequency Analysis
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Solution Overview
Problem
The rapid growth of data storage demand, exceeding the capacity for physical storage and transmission bandwidth, necessitates a highly efficient encoding method that can handle genomic data effectively, especially with the limitations of current compression techniques which either lose data quality or require significant computational resources.
Innovation Solution
A system and method for highly efficient encoding of data using asymmetric encoding/decoding and genomic encryption, incorporating a Burrow's-Wheeler transform (BWT) and frequency analysis to compress and encrypt data, allowing for random access and search within compacted datasets without decompression, and integrating distributed computing policy enforcement for enhanced security.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If traditional data compression techniques are used, then storage capacity is doubled, but data quality is degraded or lost
Solution Approach 1:
The patent segments data into fixed-size blocks and processes each block independently through frequency analysis and transformation. This segmentation allows lossless compression by preserving all original data information while organizing it into manageable units for encryption and storage.
Solution Approach 2:
The patent replaces traditional mechanical compression methods with genomic encryption techniques, using frequency analysis and Burrows-Wheeler transform to achieve compression without data loss. The system substitutes conventional compression algorithms with a multi-step process involving spectral analysis, transformation, and cryptographic encoding.
2Quantity of substance
If physical storage capacity is increased, then data storage demand is met, but manufacturing capacity is insufficient
Solution Approach 1:
The patent changes the fundamental parameter of data representation by transforming data into frequency domain representations and applying genomic encryption. This parameter transformation achieves effective storage capacity multiplication without requiring proportional increases in physical storage manufacturing.
Solution Approach 2:
The patent creates a composite encoding system that combines frequency analysis, transformation techniques, and genomic encryption methods. This composite approach achieves superior storage efficiency that cannot be obtained through single traditional compression methods, effectively increasing storage capacity without proportional manufacturing increases.
3Speed
If transmission bandwidth is increased, then data transmission capability is improved, but bandwidth bottlenecks remain
Solution Approach 1:
The patent performs preliminary compression and encryption of data blocks before transmission. By pre-processing data into compact genomic-encoded formats, the system reduces transmission bandwidth requirements and improves effective transmission speed without requiring infrastructure upgrades.
Solution Approach 2:
The patent creates compact representations of original data through frequency analysis and transformation, effectively creating a compressed copy that contains all essential information in a smaller form factor. This copying approach reduces transmission bandwidth needs while maintaining data integrity.
4Quantity of substance
If data compression is applied to multi-media data, then storage space savings decrease, but compression is still necessary
Solution Approach 1:
The patent replaces traditional compression mechanics with genomic encryption techniques that are effective across all data types including multi-media. The frequency analysis and transformation approach works universally on any data format, maintaining high compression effectiveness regardless of data type.
Solution Approach 2:
The patent creates a universal compression system that handles all data types uniformly through frequency domain analysis and genomic encoding. This multi-functional approach achieves consistent compression effectiveness across text, images, audio, and video data without requiring type-specific optimization.
5Manufacturing precision
If lossless compression is used, then all original data is retained, but compression ratio is limited to 2:1
Solution Approach 1:
The patent changes the representation parameters of data by transforming to frequency domain and applying genomic encryption. This parameter transformation achieves lossless compression ratios far exceeding the traditional 2:1 limit by exploiting statistical properties and patterns in the transformed data.
Solution Approach 2:
The patent combines multiple techniques—frequency analysis, transformation, and genomic encryption—into a composite compression system. This composite approach achieves superior lossless compression ratios by leveraging the strengths of each component method working together.
Data Source
AI summary
A system and method for data compression with genomic encryption, which uses frequency analysis on data blocks within an input data stream to produce a prefix table, representing a first layer of transformation, and which applies a Burrow's-Wheeler transform (BWT) to the data inside the prefix table, representing a second layer of transformation, and which compresses the transformed data. In some implementations, the system and method may further include applying the BWT to a conditioned stream of genomic data, wherein the conditioned stream of genomic data is accompanied by an error stream comprising the differences between the original data and the encrypted data.