Content-Agnostic File Indexing Using Permutation Indices
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Solution Overview
Problem
Existing file referencing and data compression techniques require knowledge of the data type, limiting their efficiency in indexing and reducing data size for storage and transmission.
Innovation Solution
A content-agnostic method that calculates permutations of data length and assigns an index, allowing storage and transmission of only the length and index instead of the entire data, enabling efficient retrieval of the original data.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional file referencing techniques are used, then data can be indexed and retrieved, but the system requires knowledge of data type which limits efficiency and increases complexity
Solution Approach 1:
The patent applies universality by creating a content-agnostic file referencing system that handles all data types through a single unified approach. The system uses a universal indexing mechanism based on permutation calculations that works regardless of data type, eliminating the need for type-specific handling logic and thereby reducing system complexity while maintaining productivity.
Solution Approach 2:
The patent changes the fundamental parameter of data representation by instead of storing or transmitting actual data values, the system calculates and stores only permutation indices. This parameter change from value-based storage to index-based storage dramatically improves referencing efficiency while simplifying the system architecture.
2Loss of information
If data is persisted for storage and transmission, then complete information is available, but the amount of data required increases storage and transmission costs
Solution Approach 1:
The patent extracts only the essential identifying information (permutation index) from the complete data set. Instead of persisting the entire data payload, the system extracts and stores merely the index that identifies the data's position in the permutation space, dramatically reducing data volume while preserving complete information through regenerateable data.
Solution Approach 2:
The patent creates a simplified copy or representation of the data in the form of a permutation index. This index serves as a surrogate that contains all necessary information to reconstruct or retrieve the original data, eliminating the need to store or transmit the full data set while maintaining data completeness.
3Loss of information
If data is transmitted in full form, then all information is conveyed, but transmission time and bandwidth consumption increase
Solution Approach 1:
The patent extracts only the critical permutation index from the complete data for transmission purposes. This extracted index contains all necessary information to reconstruct the original data at the receiving end, dramatically reducing transmission time and bandwidth consumption while maintaining complete information integrity.
4Productivity
If type-specific indexing methods are used, then optimization for specific data types is achieved, but the system cannot handle content-agnostic referencing
Solution Approach 1:
The patent resolves this contradiction by creating a universal indexing system based on permutation calculations that achieves both indexing efficiency and content-agnostic versatility. The mathematical foundation of permutation indexing provides optimal efficiency for any data type while simultaneously enabling the system to handle any content type without modification.
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.