Data Set Verification Using PRNG Seed Storage
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing data storage systems require large amounts of testing data for thorough verification, which is inefficient in terms of storage capacity.
Innovation Solution
A method and system for reliable data set verification that generates and regenerates data sets using a pseudo-random number generator (PRNG) to compare object contents stored in a storage system, allowing for efficient verification with minimal storage capacity requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If large amounts of testing data are stored for data set verification, then verification reliability is improved, but storage capacity requirements increase
Solution Approach 1:
The patent uses a pseudo-random number generator (PRNG) to create a compact representation (seed value and parameters) that can regenerate the entire test data set. Instead of storing large amounts of actual test data, the system stores only the copying parameters (seed, object count, object size) which can reproduce the data set on demand, significantly reducing storage requirements while maintaining verification reliability
Solution Approach 2:
The patent transforms the storage requirement from storing actual data contents to storing generating parameters. By changing from storing N objects of size S to storing a seed value and generation parameters, the system reduces storage from O(N×S) to O(1), enabling verification reliability without proportionally increasing storage capacity
Data Source
AI summary
A computer program product, system, and method for generating a test data set using object count and object size parameters, storing the generated data set in storage, subsequently regenerating the data set, and comparing the regenerated data set to the stored data set to validate the storage.