Codebook-Based Data Encoding With Multi-Library Compaction
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current data storage technologies are struggling to keep pace with the exponential growth in data storage demand, leading to a shortage of physical storage capacity and limitations in transmission bandwidth. Additionally, existing data encoding methods rely on a single encoding algorithm, which compromises data compaction and security.
Innovation Solution
The system employs a codebook-based data encoding method that uses multiple codebooks to maximize data compaction and enhance security. Each portion of the data is encoded using different compaction algorithms and sourceblock sizes, requiring multiple decoding libraries and knowledge of sourceblock lengths for proper decoding.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If a single encoding algorithm is used for all data, then decoding is simplified and requires only a single algorithm, but data compaction is not maximized and security is compromised
Solution Approach 1:
The patent divides the data into multiple portions and applies different encoding algorithms to each portion. Each portion is encoded independently with its own algorithm, creating segmented encoded data that requires corresponding segmented decoding operations. This segmentation allows optimization of compaction for each data type while maintaining manageable decoding through structured organization.
Solution Approach 2:
The patent applies different encoding algorithms to different portions of data based on their specific characteristics. Each data portion receives a locally optimized encoding approach suited to its type and properties, rather than applying a uniform encoding method across all data. This local quality approach maximizes overall compaction efficiency.
2Device complexity
If a single encoding algorithm is used for all data, then the encoding process is simplified, but maximum data compaction cannot be achieved
Solution Approach 1:
The patent implements a dynamic encoding system that selects and applies different encoding algorithms based on the characteristics of each data portion. The system adapts its encoding approach dynamically rather than using a static single algorithm, allowing optimization of compaction rates for different data types while managing complexity through structured selection criteria.
Solution Approach 2:
The patent changes encoding parameters and algorithm selection based on data characteristics. Different portions of data are encoded with different parameters and algorithms optimized for their specific properties, allowing maximum compaction achievement while managing system complexity through parameter-based differentiation.
3Ease of manufacture
If a single encoding algorithm is used for all data, then implementation is easier, but security is compromised because all data can be decoded using a single algorithm
Solution Approach 1:
The patent segments the encoding system into multiple independent algorithm components, each applied to different data portions. This segmentation creates security layers where compromise of one algorithm does not expose all data, as each segment requires its own specific decoding algorithm. The segmented structure maintains implementation feasibility through modular design.
Solution Approach 2:
The patent creates a composite encoding system that combines multiple different encoding algorithms into a unified security framework. Like composite materials that combine different substances for enhanced properties, this composite approach combines multiple algorithms to achieve security properties that a single algorithm cannot provide, while maintaining implementation ease through structured integration.
Data Source
AI summary
A system and method for codebook-based data encoding. Portions of the data are encoded by different encoding libraries, depending on which library provides the greatest compaction for a given portion of the data. This methodology not only provides substantial improvements in data compaction over use of a single data compaction algorithm with the highest average compaction, but provides substantial additional security in that multiple decoding libraries must be used to decode the data. In some embodiments, each portion of data may further be encoded using different sourceblock sizes, providing further security enhancements as decoding requires multiple decoding libraries and knowledge of the sourceblock size used for each portion of the data. In some embodiments, encoding libraries may be randomly or pseudo-randomly rotated to provide additional security.