Infrastructure Failure Predictor Using Historical Relationship Indexing
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Solution Overview
Problem
Conventional risk assessment for technology infrastructure changes focuses on data related to the change itself rather than historical relationships between physical devices, applications, and individuals involved, leading to inadequate prediction of failure risks.
Innovation Solution
A predictive modeling apparatus and method that uses machine-readable memory and processors to create an index for infrastructure changes based on historical data, including infrastructure change identifiers, device identifiers, and application identifiers, to predict failure rates by analyzing relationships and correlations between change elements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional risk assessment focuses on data surrounding the infrastructure change itself, then the assessment process is simple and straightforward, but the prediction accuracy of failure risk is insufficient
Solution Approach 1:
The patent segments the risk assessment into multiple dimensions: change characteristics, historical relationships between physical devices, applications, and individuals, and contextual factors. This segmentation allows comprehensive analysis without overwhelming complexity by organizing data into manageable categories that can be processed systematically.
Solution Approach 2:
The patent transitions from traditional one-dimensional assessment (change data only) to multi-dimensional assessment by incorporating historical relationships across different entities (devices, applications, individuals). This dimensional expansion enables more accurate failure risk prediction by considering interactions across multiple axes of the infrastructure ecosystem.
2Reliability
If historical relationships between physical devices, applications and individuals are analyzed, then failure risk prediction improves, but the data processing complexity increases
Solution Approach 1:
The patent performs preliminary actions by pre-processing and organizing historical relationship data before actual risk assessment. This includes establishing baseline relationships between devices, applications, and individuals, and pre-calculating interaction patterns. These preliminary structures enable faster, more efficient risk prediction when actual changes occur.
Solution Approach 2:
The patent introduces intermediary data structures that mediate between raw historical data and risk prediction outputs. These intermediaries include relationship graphs, interaction matrices, and contextual profiles that simplify complex historical relationships into manageable formats for analysis, reducing processing complexity while maintaining prediction accuracy.
Data Source
AI summary
Apparatus and methods for reducing infrastructure failure rates. The apparatus and methods may compile and store data related to the physical devices and applications associated with an infrastructure change. Variables may be derived from the stored data using a range of methods and multiple variable values may be consolidated. A model may be developed based on the values and relationships of the derived variables. The model may be applied to assess the risk of a prospective infrastructure change.