Computational Random Number Generation via Asynchronous Threads
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Solution Overview
Problem
Existing random-number generators often rely on specialized circuitry or single signal sources, which can be unreliable and difficult to detect for non-randomness, and may not be accessible in all computational environments.
Innovation Solution
The proposed method generates sequences of random numbers based on nondeterministic phenomena computationally initiated and accessed within a computer system, utilizing multiple asynchronous threads or computational entities to achieve unpredictability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If specialized circuitry or single signal sources are used for random number generation, then the generation process can be implemented, but the system becomes unreliable and difficult to detect for non-randomness
Solution Approach 1:
The patent divides the random number generation process into multiple independent computational threads instead of relying on a single specialized circuit or signal source. Each thread independently generates random numbers using standard computational resources, and the results are combined. This segmentation eliminates single-point failures and removes the need for specialized circuitry while maintaining reliability.
2Adaptability or versatility
If specialized circuitry is used for random number generation, then random numbers can be produced, but the system may not be accessible in all computational environments
Solution Approach 1:
The patent implements random number generation using universal computational resources available in all standard computational environments, including multi-core processors, hyper-threading capabilities, and standard library functions. By using universally available features rather than specialized circuitry, the system achieves broad adaptability across different platforms and environments.
3Reliability
If multiple asynchronous threads are used to generate random numbers computationally, then robustness against single-point failures is achieved, but the computational overhead increases
Solution Approach 1:
The patent merges the random number generation operations of multiple asynchronous threads into a unified output stream. By combining the results from multiple threads that are already executing for other computational purposes, the system achieves robustness against single-point failures without significant additional computational overhead, as the threads are performing useful work regardless of their random number generation contribution.
Data Source
AI summary
The current document is directed to methods and systems that generate sequences of random numbers. Unlike many currently available random-number generators that continuously measures a physical apparatus or other signal source, the currently disclosed methods and systems employ nondeterministic phenomena that are computationally initiated and computationally accessed within a computer system. The nondeterministic phenomena are often a produced by multiple simultaneously executing, asynchronous threads or other computational entities, with the unpredictability arising from multiple different types and sources of nondeterministic behavior within the computer system. Unlike pseudorandom-number generators, statistics and metrics computed from sequences of random numbers produced by the currently disclosed random-number generators have values close to those expected for a random-selection process. Unlike random numbers that depend on specialized circuitry or single signal sources, the currently disclosed random-number generators used standard components and significant redundancy and robustness to single-point failures.