Consistent Structured Data Hash Generation Across Formats
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Solution Overview
Problem
Information handling systems face inefficiencies due to 'false positives' when comparing structured data in different formats, leading to unnecessary computational activity and resource usage, as different data formats result in different hash values despite representing the same data.
Innovation Solution
A method is introduced to generate consistent structured data hash values across platforms and formats by identifying data segments, expressing them in a standard format, applying a hash algorithm to produce segment hash values, assembling an aggregate hash code, and confirming its association with the data set, thereby reducing erroneous change detections.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If hash functions are used to map structured data to fixed-length hash codes for efficient data evaluation, then computational efficiency is improved, but false positives occur when the same data is represented in different formats, causing unnecessary computational activity and reducing system reliability
Solution Approach 1:
The patent segments the structured data into atomic data segments (individual fields, values, and their relationships) before hashing. This segmentation allows the system to normalize and hash only the essential data content rather than the entire formatted structure, enabling consistent hash values across different formats while maintaining computational efficiency.
Solution Approach 2:
The patent introduces a normalization step as an intermediary process between data representation and hashing. This intermediary converts various structured data formats into a standardized internal representation before applying the hash function, thereby eliminating format-dependent hash variations and reducing false positives without sacrificing performance.
2Adaptability or versatility
If different structured data formats (JSON, XML, CSV) are used to represent the same data, then adaptability and versatility are improved, but hash values become inconsistent, causing false positives and increasing resource requirements
Solution Approach 1:
The system segments data into atomic units and normalizes them independently of their original format. By processing only the essential semantic content rather than the entire formatted structure, the system achieves format independence while consuming fewer resources compared to full-format conversion approaches.
Solution Approach 2:
The patent extracts the essential data content from various formatted representations and discards the format-specific syntax. This extraction process creates a format-independent canonical representation that can be consistently hashed, eliminating the need to process entire formatted documents and thereby reducing computational resource consumption.
3Device complexity
If traditional hash functions are applied to structured data in different formats, then simplicity of implementation is maintained, but false positives cause unnecessary cache updates and notifications, reducing system speed
Solution Approach 1:
The patent performs preliminary normalization of the data structure before hashing. This preliminary action transforms varied formatted data into a consistent internal representation, ensuring that subsequent hash operations produce correct results without requiring complex format-specific handling logic, thereby maintaining implementation simplicity while improving speed.
Solution Approach 2:
The system creates a normalized copy of the data structure that represents the essential content independent of the original format. This normalized copy is then hashed, allowing the system to maintain simple hash implementation while avoiding false positives that would trigger unnecessary cache updates and notifications, thus improving operational speed.
Data Source
AI summary
Methods, information handling systems and computer readable media are disclosed for generation of consistent structured data hash values across platforms and structured data formats. In one embodiment, a method includes identifying, at an information handling system, a set of data segments within a set of structured data and expressing the set of structured data in a standard format. This embodiment of the method further includes, for each of the data segments within the set of data segments, applying a hash algorithm to produce a data segment hash value and obtaining a standardized identifier for the data segment. The method continues with assembling an aggregate hash code comprising the standardized identifier and the data segment hash value for each of the data segments, and confirming an association of the aggregate hash code with the set of structured data.