Non-compressible Data Stream Generation via Prime Number Sequences
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Solution Overview
Problem
Conventional methods for generating testing data are inefficient, particularly due to the slowness of hashing and cryptography techniques, and the need for maintaining a master copy of data streams for verification, which can be costly and impractical. Additionally, data compression in testing environments may not be desirable, especially when preserving the original data size is necessary.
Innovation Solution
The use of prime numbers to generate non-compressible data streams through an initialization parameter and constrained prime numbers, allowing for high-speed data stream generation and verification without a master copy, while maintaining the original data size by interleaving sequences to create unique and deduplicatable data streams.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If hashing and cryptography techniques are used to generate testing data, then data can be generated for testing purposes, but the generation process becomes slow and inefficient
Solution Approach 1:
The patent changes the fundamental parameters of data generation by using linear congruential generators with carefully selected prime numbers instead of cryptographic hashing. This parameter change maintains data uniqueness and reliability while dramatically improving generation speed, as the linear congruential method requires only simple arithmetic operations rather than computationally intensive hashing algorithms.
Solution Approach 2:
The patent employs disposable pseudo-random sequences generated by linear congruential generators that can be quickly created and discarded. Each sequence is generated on-demand using simple arithmetic operations, eliminating the need for expensive cryptographic operations while ensuring each testing data set remains unique and non-compressible.
2Reliability
If a master copy of data stream is maintained for verification, then data integrity can be verified, but storage cost and complexity increase
Solution Approach 1:
The patent implements self-service verification where the data stream carries within itself the means for verification through embedded checksums and sequence identifiers. The linear congruential generator parameters (prime numbers, modulus, increment) serve as self-describing metadata that enable verification without requiring external master copies, allowing the data to verify itself.
Solution Approach 2:
The patent extracts the essential verification information (checksums, sequence identifiers, generator parameters) from the master copy concept and embeds it directly within the data stream. This extraction eliminates the need to store complete master copies while retaining the critical verification capabilities, reducing storage requirements to only the essential metadata.
3Loss of energy
If data is compressed before transmission, then network bandwidth is reduced, but original data size is lost which is undesirable in testing environments
Solution Approach 1:
The patent applies preliminary anti-action by generating data that is inherently non-compressible through the use of linear congruential generators with prime number moduli. The generated data exhibits uniform distribution and high entropy characteristics that prevent compression algorithms from reducing its size. This preliminary design ensures that no compression is needed or beneficial, maintaining original data size while optimizing other transmission parameters.
Data Source
AI summary
Generating non-compressible data streams is disclosed, including: receiving an initialization parameter; determining a constrained prime number, wherein the constrained prime number comprises a plurality of component values, wherein each of the plurality of component values comprises a prime number, wherein each of the plurality of component values is different; and generating a non-compressible sequence based at least in part on the initialization parameter and the constrained prime number.