Sequence Block Encoding for Bandwidth-Efficient Data Compaction
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Solution Overview
Problem
The rapid growth of data storage demand, particularly with the rise of social media, cloud data centers, and genomic data, has outpaced the capacity for physical storage and transmission bandwidth, leading to a need for efficient and secure data encoding and storage solutions, especially as quantum computing poses risks to existing encryption technologies.
Innovation Solution
A system and method for bandwidth-efficient data encoding that involves a sequence analyzer to identify unique characters in datasets, deconstruct them into sourceblocks at specific positions, and encode these blocks using a data deconstruction engine and library management module to assign reference codes, enabling secure and compact storage and transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If data compression is used to increase storage capacity, then storage efficiency improves, but data integrity deteriorates due to lossy compression or the compression ratio is insufficient at only 2:1
Solution Approach 1:
The patent segments data into fixed-size blocks and processes each block independently through encryption and compression. This segmentation allows the system to achieve higher compression ratios while maintaining data integrity, as each block can be optimally compressed without affecting other blocks. The block-based approach enables lossless compression to achieve better than 2:1 ratios while preserving complete data integrity.
Solution Approach 2:
The patent replaces traditional mechanical compression algorithms with a cryptographic-based compression system. By using encryption transformations and mathematical operations instead of conventional compression mechanics, the system achieves superior compression ratios while guaranteeing data integrity through the reversible nature of cryptographic operations.
2Quantity of substance
If physical storage capacity is increased to meet demand, then storage availability improves, but manufacturing capacity worsens as it cannot keep pace with exponential data growth
Solution Approach 1:
The patent fundamentally changes the parameter of data representation by transforming raw data into compressed cryptographic forms. This parameter change reduces the physical storage capacity requirement from 1 zettabyte to potentially much less, allowing existing manufacturing capacity to meet storage demands without requiring exponential increases in physical production.
Solution Approach 2:
The patent creates efficient digital representations of data through compression and encryption, where the compressed data structure serves as a more efficient copy that requires less physical storage. This digital transformation allows existing storage infrastructure to accommodate growing data volumes without proportional increases in physical manufacturing capacity.
3Speed
If transmission bandwidth is increased to handle large datasets, then data transmission speed improves, but infrastructure cost worsens due to the exponential growth of bandwidth requirements
Solution Approach 1:
The patent segments large datasets into smaller compressed blocks for transmission. This segmentation reduces the total bandwidth requirement while maintaining transmission speed, as each compressed block can be transmitted efficiently and reassembled at the destination. The block-based approach enables parallel transmission of multiple smaller units, improving overall data throughput without requiring proportional increases in total bandwidth capacity.
Solution Approach 2:
The patent changes the size parameter of transmitted data through compression and encryption transformations. By transforming data into more compact representations before transmission, the system achieves high effective transmission speeds without requiring increased physical bandwidth infrastructure, thereby avoiding the exponential cost growth associated with bandwidth expansion.
4Reliability
If existing encryption technologies are used to protect data, then security is provided, but security reliability deteriorates as quantum computing becomes imminent
Solution Approach 1:
The patent employs post-quantum cryptographic algorithms that are designed to resist quantum computing attacks. By changing the cryptographic parameters and mathematical foundations from classical to quantum-resistant algorithms, the system maintains security reliability while adapting to the emerging quantum computing threat landscape.
Solution Approach 2:
The patent inverts the traditional encryption approach by using compression before encryption rather than encryption before compression. This inversion optimizes the system for both security and efficiency, as the compressed data requires fewer cryptographic operations while maintaining the same security level, and the approach is compatible with quantum-resistant algorithms.
Data Source
AI summary
A system and methods for bandwidth-efficient data encoding comprising a sequence analyzer configured to: analyze a received sequence dataset to determine a sequence dataset file type, scan the sequence dataset to maintain a count of unique characters contained therein, identify positions where the unique character count increases by a power of two, deconstruct the sequence dataset into a plurality of sourceblocks at the identified positions, and encode the plurality of sourceblocks using a data deconstruction engine and library management module to assign each sourceblock a reference code.