Dynamic Noise Source Selection for Random Number Generation

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Solution Overview

Problem

Existing random number generation systems face challenges in evaluating and maintaining the quality of individual noise sources, leading to unpredictable entropy quality and potential degradation, which affects the reliability of generated random numbers.

Innovation Solution

A system that configures a mapper to feed inputs from a subset of noise sources, continuously evaluates their quality, and replaces degraded sources with higher-quality ones from a pool, ensuring that only noise sources meeting predetermined criteria contribute to the random number generation, thereby maintaining consistent entropy quality.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Productivity

If multiple noise sources are continuously used to generate random numbers, then the productivity of random number generation is improved, but the quality of entropy degrades over time due to noise source degradation

Engineering Contradiction:

Improverandom number generation throughputVSAvoidentropy quality

Core Design Contradiction:

ProductivityVSReliability

Solution Approach 1:

The system dynamically selects and switches between multiple noise sources based on their real-time quality assessments. The controller continuously monitors entropy quality metrics and reconfigures the mapper to use only high-quality noise sources, making the system adaptive to degradation over time while maintaining both productivity and reliability.

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system changes the operational parameters of noise sources by adjusting which sources are active in the mapper configuration. By evaluating entropy quality parameters and switching between different noise source combinations, the system maintains optimal entropy quality while continuously generating random numbers.

Inventive Principle:

Principle #35Parameter changes

2Reliability

If noise sources are evaluated and replaced based on quality criteria, then the reliability of random number generation is improved, but the device complexity increases due to continuous monitoring and switching mechanisms

Engineering Contradiction:

Improveentropy quality consistencyVSAvoidquality evaluation and switching system

Core Design Contradiction:

ReliabilityVSDevice complexity

Solution Approach 1:

The system performs self-diagnosis and self-reconfiguration by automatically evaluating the quality of its own noise sources and switching between them without external intervention. The controller monitors entropy quality metrics and autonomously reconfigures the mapper to maintain reliable random number generation, reducing the need for external management complexity.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system implements a feedback mechanism where entropy quality is continuously evaluated and used to control the selection of noise sources. The quality assessment results feed back to the controller, which adjusts the mapper configuration accordingly, creating a closed-loop system that maintains reliability through automated quality control.

Inventive Principle:

Principle #23Feedback

3Duration of action of moving object

If a subset of noise sources is actively used, then the lifespan of individual noise sources is extended, but the measurement precision of entropy quality becomes more difficult to maintain

Engineering Contradiction:

Improvenoise source lifespanVSAvoidentropy quality assessment accuracy

Core Design Contradiction:

Duration of action of moving objectVSMeasurement precision

Solution Approach 1:

The system performs preliminary evaluation of alternative noise sources before they are needed, maintaining a pool of pre-assessed noise sources with known quality characteristics. This allows the controller to quickly switch to validated sources when degradation is detected, extending lifespan while maintaining measurement precision through advance preparation.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system evaluates more noise sources than are simultaneously active, maintaining a reserve pool of evaluated sources. By evaluating a larger number of sources partially (in terms of evaluation depth) rather than fully characterizing all sources at once, the system extends noise source lifespan while maintaining sufficient measurement precision for reliable operation.

Inventive Principle:

Principle #16Partial or excessive action

Data Source

PatentUS11301215B2Real time configuration of multiple true random number generator sources for optimized entropy generation

Publication Date: 2022.04.12 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

A computer-implemented method for generating one or more random numbers includes configuring a mapper to feed inputs of a random number generation system using a subset of noise sources from multiple noise sources. The random number generation system generates a random number based on the inputs. The method further includes evaluating the subset of noise sources and detecting that a first noise source from the subset of noise sources has degraded in quality. The method further includes evaluating a second noise source from the available noise sources, the second noise source not being in the subset of noise sources. In response to the second noise source satisfying a predetermined threshold criterion, the first noise source is replaced with the second in the subset of noise sources for providing random bit streams to facilitate generating the random number by the random number generation system.