Binary File Referencing with Length and Permutation Indexing
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Solution Overview
Problem
Existing file referencing and data compression techniques require knowledge of the data type, limiting their efficiency in reducing storage and transmission requirements.
Innovation Solution
A content-agnostic method that analyzes data to determine its length, generates all permutations of that length, and stores or transmits only the length and index of the data, allowing for efficient retrieval of the original data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If traditional file referencing techniques are used, then data can be indexed and retrieved, but the system requires knowledge of data type and stores significant amounts of metadata
Solution Approach 1:
The patent extracts only the essential identifying information (hash value and length) from the original data, storing merely the index rather than the complete data representation. This extraction approach reduces storage requirements while maintaining retrieval capability, directly addressing the contradiction between information preservation and storage efficiency.
Solution Approach 2:
The system creates a simplified copy (index entry) that references the original data through a hash value rather than storing the complete data structure. This copying mechanism allows efficient storage and retrieval without requiring complex metadata about data types, resolving the contradiction between comprehensive data representation and storage efficiency.
2Adaptability or versatility
If content-specific indexing methods are used, then indexing accuracy is improved, but the system cannot handle arbitrary content types
Solution Approach 1:
The patent implements a universal indexing mechanism using hash functions that can process any data type (text, binary, images, videos) without requiring content-specific algorithms. The hash function serves multiple purposes: uniqueness verification, indexing, and retrieval across all content types, achieving both versatility and sufficient accuracy for file referencing.
3Quantity of substance
If complete data is stored for retrieval, then retrieval accuracy is ensured, but storage and transmission requirements increase
Solution Approach 1:
The system extracts only the critical identifying elements (hash value and length) needed for reliable retrieval, discarding redundant metadata. This extraction maintains retrieval reliability by preserving the unique identifier while minimizing stored data volume, directly resolving the contradiction between data volume and retrieval reliability.
Solution Approach 2:
The hash value serves as an intermediary that connects the stored index to the original data without requiring storage of the complete data structure. This intermediary mechanism ensures reliable retrieval through unique identification while dramatically reducing the quantity of stored substance.
Data Source
AI summary
A computer-implemented method for content-agnostic referencing of a binary data file, the method comprising: determining a length of the binary data file, the length comprising the number of bits of the binary data file; for the determined length, generating all permutations of data of the determined length; locating an index within the generated permutations, wherein the index is the starting position of the binary data file within the generated permutations; and using the length and the index to indicate the binary data file.