Dynamic Symptom-Condition Correlation Mappings
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Solution Overview
Problem
Existing tools lack an effective method to correlate computer system symptoms with conditions, leading to inefficient identification and resolution of support issues in computer systems, as they rely on static mappings that are not validated with real-time feedback data.
Innovation Solution
A correlation information system that receives user input to define rules linking symptoms to conditions, collects feedback data from client agents, analyzes this data to produce correlation information, and refines mappings by quantifying the degree of correlation between symptoms and conditions, allowing for dynamic adjustment and distribution of these mappings to client systems.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If static mappings are used to correlate symptoms with conditions, then the system structure is simple, but the accuracy and relevance of symptom-condition correlations deteriorates
Solution Approach 1:
The patent implements dynamic symptom-condition mappings by continuously collecting feedback data from client systems and using this data to refine and update the correlation mappings. The system transitions from static mappings to dynamic mappings that adapt to real-time system behavior, thereby improving accuracy while managing complexity through automated feedback loops.
Solution Approach 2:
The patent introduces feedback mechanisms where client systems provide feedback data about symptom occurrences and condition states. This feedback is used to validate and refine the symptom-condition mappings, creating a self-improving system that continuously enhances correlation accuracy based on actual system performance data.
2Measurement precision
If feedback data is collected from all client systems, then the correlation information becomes more accurate, but the data collection overhead and processing requirements increase
Solution Approach 1:
The patent applies local quality by collecting feedback data selectively based on the specific symptom-condition mappings being evaluated. Rather than collecting all possible data uniformly, the system focuses data collection on relevant parameters for each mapping rule, improving precision while reducing unnecessary data collection overhead.
Solution Approach 2:
The system implements partial data collection by only gathering feedback data for client systems and parameters that are relevant to the current mapping validation needs. This selective approach avoids excessive data collection while still achieving sufficient precision for accurate correlation information.
3Adaptability or versatility
If multiple feedback data types are collected from client agents, then the correlation analysis becomes more comprehensive, but the complexity of data processing and analysis increases
Solution Approach 1:
The patent segments feedback data into distinct types and categories corresponding to different symptom-condition mappings. Each data type is processed and analyzed separately according to its specific requirements, making the overall complex data processing task manageable through modular segmentation of data collection and analysis operations.
Data Source
AI summary
Feedback data can be received from client agents running on client computer systems. The feedback data can include data on the symptoms and conditions for rules that relate computer system symptoms to computer system conditions. The feedback data can be analyzed to produce correlation information that quantifies a degree of correlation between the symptom(s) and condition(s) related by the rule(s). It may be determined whether analysis of the feedback data warrants including one of the rules in correlation mappings to be applied to monitored computer systems. If so, then that rule can be included in the mappings. Information representing the correlation mappings may be transmitted to the monitored computer system(s). Additionally, information representing the correlation mappings may be transmitted to the monitored computer system(s), and types of feedback data collected from the client agents can be altered on the basis of the correlation information.