Automated Computer Repair Ordering via Entity Relationship Analysis
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Solution Overview
Problem
Existing computer systems face challenges in efficiently monitoring their health and determining the optimal order of repairs to maintain performance and data redundancy during maintenance, as current methods lack comprehensive analysis of entity relationships and safety considerations.
Innovation Solution
A rules-based engine monitors the health of computer systems, identifies problem entities and their relationships, determines relationship types (containment, composition, aggregation), and analyzes these to suggest an order of repairs that prioritizes safety and performance, presenting alerts for user action or automated execution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If comprehensive monitoring and relationship analysis is performed to determine optimal repair order, then system safety and performance are improved, but device complexity and analysis time increase
Solution Approach 1:
The system segments the computer system into distinct entities (storage devices, servers, databases) and their relationships, allowing comprehensive monitoring without overwhelming complexity. Each entity can be monitored independently while relationships provide context for repair prioritization.
Solution Approach 2:
The system performs preliminary monitoring and relationship mapping continuously, so when a problem occurs, the repair order can be determined immediately without complex real-time analysis. The foundation of entity relationships is established in advance.
2Reliability
If repair order is determined based on comprehensive relationship analysis, then data redundancy and performance are maintained, but time for analysis and alert generation increases
Solution Approach 1:
The system continuously maintains a model of entity relationships and their importance levels in advance. When a problem occurs, this pre-established model allows immediate determination of repair priority without time-consuming real-time analysis, ensuring data redundancy is maintained.
Solution Approach 2:
The system incorporates feedback from monitoring data about actual system performance and redundancy status, continuously refining the repair priority model to better reflect real-time conditions while maintaining efficient analysis speed.
3Productivity
If automated monitoring and repair ordering is implemented, then productivity of repair operations is improved, but device complexity increases
Solution Approach 1:
The system performs self-monitoring and self-diagnosis, automatically identifying problems and determining repair priorities without requiring constant human intervention. This automation improves repair productivity while the modular design keeps complexity manageable.
Solution Approach 2:
The monitoring and analysis system serves multiple functions: detecting problems, mapping relationships, determining priority, and generating alerts. This multi-functionality consolidates what would otherwise be separate complex systems into a unified platform.
Data Source
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AI summary
Monitoring the health of a computer system and suggesting an order of repair when problems within the computer system have been identified. Problem(s) and problem entity(s) within the computer system are identified during monitoring. Relationship(s) of the problem entities with other entities in the computer system are identified. A relationship type for each of the identified relationship(s) is determined. A combination of the identified problem(s), the identified problem entity(s), and the determined relationship type(s) is analyzed to determine an order in which repairs of one or more user-visible entities of the computing system should occur in order to address the identified problem(s). An alert comprising the determined order of the repairs is then presented to a user.