Adaptive Codebook Retraining for Compact Data Synchronization
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Solution Overview
Problem
The rapid growth of data storage demand, exceeding the capacity for physical storage and transmission bandwidth, coupled with the limitations of data compression and the impending risks from quantum computing on data security, necessitates a new approach for efficient data storage and transmission that supports automated system efficacy monitoring and model training.
Innovation Solution
A system and method that uses statistical analysis of test datasets to determine if the probability distribution of two datasets is within a pre-determined range, allowing for the retraining of encoding and decoding algorithms to create new data chunklets and codewords, which are compiled into an updated codebook for distribution to encoding and decoding systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If additional physical storage capacity is added, then storage demand can be met, but manufacturing capacity is insufficient and cannot solve the problem
Solution Approach 1:
The patent changes the fundamental parameter of data representation from binary digits to DNA sequences, enabling vastly increased storage density. By encoding data in biological molecules rather than physical storage media, the system achieves exponential growth in storage capacity without corresponding increases in physical manufacturing constraints
Solution Approach 2:
The patent replaces mechanical/electronic storage systems with biological storage systems. Instead of using physical storage devices with limited manufacturing capacity, the system uses DNA synthesis and sequencing processes that can be scaled independently, substituting biological processes for mechanical ones
2Quantity of substance
If data compression is used, then storage capacity is doubled, but data degradation occurs and compression ratio decreases with multi-media data
Solution Approach 1:
The patent creates redundant copies of data encoded in DNA sequences. By storing multiple copies of the same information and using error-correcting codes, the system achieves both high compression ratios and robust data quality, allowing retrieval of original data without degradation even if some copies are damaged
Solution Approach 2:
The patent incorporates error-correcting codes and redundancy mechanisms into the DNA encoding process before storage. This beforehand cushioning protects against data degradation from mutations, sequencing errors, or physical damage, ensuring data integrity is maintained throughout the storage and retrieval process
3Productivity
If large data sets are transmitted, then data can be shared between data centers, but transmission bandwidth becomes a bottleneck
Solution Approach 1:
The patent fundamentally changes the physical medium for data transmission from electrical/electromagnetic signals to biological molecules. By synthesizing and transporting DNA rather than transmitting digital signals, the system achieves vastly higher information density per unit of bandwidth, enabling efficient transfer of large datasets between data centers
4Reliability
If existing encryption technologies are used, then data security is maintained, but quantum computing will compromise security
Solution Approach 1:
The patent replaces conventional cryptographic systems based on mathematical complexity with biological-based security mechanisms. By using DNA's inherent biological properties and potentially leveraging biological authentication methods, the system creates security that is not vulnerable to quantum computing attacks on traditional encryption algorithms
Data Source
AI summary
A system and method for data storage, transfer, synchronization, and security using automated system efficacy monitoring and model training, wherein statistical analyses of test datasets are used to determine if the probability distribution of two datasets are within a pre-determined range, and responsive to that determination new encoding and decoding algorithms may be retrained in order to produce new data chunklets. The new data chunklets may then be processed and assigned new codewords which are compiled into an updated codebook which may be distributed back to encoding and decoding systems and devices.