Correlation Model Update for Operations Management
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Solution Overview
Problem
Existing operations management systems face inefficiencies in regenerating correlation models when system configurations or monitoring policies change, leading to prolonged processing times when new metrics are added.
Innovation Solution
An operations management apparatus and method that includes correlation model updating capabilities, where existing correlations are leveraged to quickly generate a new model by excluding already-judged pairs and adding detected correlations to the existing model.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a correlation model is regenerated from scratch when a new metric is added, then the correlation model is complete and accurate, but the processing time becomes excessively long
Solution Approach 1:
The patent segments the correlation model regeneration process into two parts: (1) retaining the existing correlation model for already-monitored metrics, and (2) only regenerating correlations involving the new metric. This segmentation avoids reprocessing the entire correlation matrix when a single metric is added, thereby reducing computation time while maintaining model completeness.
Solution Approach 2:
The patent performs preliminary action by pre-establishing correlation models for existing metrics before a new metric is added. When a new metric is introduced, the system leverages the pre-existing correlation model and only computes new correlations involving the added metric, rather than regenerating all correlations from scratch. This preliminary preparation significantly reduces the regeneration time.
2Reliability
If all pairs of metrics are evaluated when updating the correlation model, then the correlation model is fully updated, but the processing speed decreases
Solution Approach 1:
The patent extracts the necessary computation scope by identifying and evaluating only the pairs of metrics that involve the newly added metric. The system extracts the subset of correlations that need to be recomputed (those involving the new metric) and leaves the rest of the correlation model unchanged. This extraction approach maintains accuracy for the updated portion while significantly improving overall update speed.
Data Source
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AI summary
A correlation model is updated quickly in the case that monitored metrics are changed. The correlation model storing unit 112 stores a first correlation model including a correlation detected for a pair of metrics in first plural metrics. The correlation model updating unit 103, in the case that a metric is added, judges existence of a correlation for each of pairs of metrics obtained by excluding the pair of metrics in first plural metrics from pairs of metrics in second plural metrics including the added metric and the first plural metrics, and generates a second correlation model by adding the detected correlation to the first correlation model.