Prioritizing Call Home Data for Computing Systems

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Solution Overview

Problem

Current methods for prioritizing call home data often result in important problem analysis data being omitted, leading to additional support costs and customer downtime, as well as potential data loss due to pruning or deletion over time.

Innovation Solution

A method that determines the priority of problem analysis data based on usage data of previous problem analysis data associated with a defect, the size of the problem analysis data, and a confidence score, thereby deciding whether to include it in a data collection.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Quantity of substance

If problem analysis data is collected without prioritization, then complete data is available for defect analysis, but data size increases and important data may be omitted due to storage constraints

Engineering Contradiction:

Improvedata sizeVSAvoiddata completeness

Core Design Contradiction:

Quantity of substanceVSReliability

Solution Approach 1:

The system performs preliminary prioritization of problem analysis data before collection by evaluating usage data of previous problem analysis, size of current data, and confidence scores. This preliminary action determines which data should be included in the data collection, preventing important data from being omitted while managing storage constraints.

Inventive Principle:

Principle #10Preliminary action

2Quantity of substance

If data collection is limited to reduce storage requirements, then data size is controlled, but important problem analysis data may be omitted leading to additional support costs

Engineering Contradiction:

Improvedata sizeVSAvoidsupport time

Core Design Contradiction:

Quantity of substanceVSLoss of time

Solution Approach 1:

The system uses feedback from usage data of previous problem analysis data and confidence scores to dynamically determine priority values. This feedback mechanism ensures that data selection is based on actual usage patterns and effectiveness, reducing unnecessary data collection while maintaining support efficiency.

Inventive Principle:

Principle #23Feedback

3Quantity of substance

If problem analysis data is pruned or deleted over time, then storage space is freed, but critical data may be lost

Engineering Contradiction:

Improvestorage spaceVSAvoiddata loss

Core Design Contradiction:

Quantity of substanceVSLoss of information

Solution Approach 1:

The system performs preliminary prioritization before data collection, using usage data and confidence scores to determine which data is most important. This preliminary action ensures that critical data is identified and collected first, preventing data loss while managing storage space through selective collection rather than post-collection pruning.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS20250138929A1Prioritization of call home data

Publication Date: 2025.05.01 INTERNATIONAL BUSINESS MACHINE CORPORATION

AI summary

Problem analysis data associated with a defect of a computing system is received. A priority value of the problem analysis data is determined based on usage data of previous problem analysis data associated with the defect, a size of the problem analysis data, and a confidence score associated with the previous problem analysis data. The problem analysis data is determined to be included in a data collection based on the priority value. The problem analysis data is stored in the data collection.