Hierarchical Server System for Automated Error Resolution
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Solution Overview
Problem
Existing computer systems and networks, such as utility grid networks, lack the capability to automatically detect, isolate, and resolve errors, and do not enable continuous learning to address new error solutions.
Innovation Solution
A self-learning algorithm-based system that continuously monitors for errors, isolates them locally when possible, and uses a hierarchical server structure to determine and implement solutions, with local and central servers collaborating to analyze and store error and solution data for future reference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If automated diagnostic data transfer and analysis is implemented, then error detection capability is improved, but system complexity increases
Solution Approach 1:
The system divides error detection and analysis into multiple levels: local servers handle immediate error detection and basic analysis, while central servers perform comprehensive analysis and solution generation. This segmentation allows error detection capability to improve without proportionally increasing overall system complexity, as each segment handles only its designated functions.
Solution Approach 2:
The patent introduces automated diagnostic software as an intermediary component that collects error data from multiple sources, transfers it to appropriate servers for analysis, and implements solutions. This intermediary layer simplifies the overall system architecture by providing a standardized interface between error sources and analysis mechanisms, reducing the complexity burden.
2Adaptability or versatility
If continuous learning and adaptation is implemented, then error resolution effectiveness is improved, but computational resource requirements increase
Solution Approach 1:
The system performs preliminary error analysis and solution development in advance by continuously learning from accumulated error data. Central servers analyze error patterns and prepare solution templates beforehand, so when actual errors occur, pre-computed solutions can be quickly applied. This reduces real-time computational resource requirements while maintaining high adaptability.
Solution Approach 2:
The system implements self-learning capabilities where the automated diagnostic software and servers continuously analyze error data and improve their own problem-solving abilities without requiring external intervention. The system serves itself by automatically updating its knowledge base and refining solution strategies, improving error resolution effectiveness while managing computational resources through autonomous optimization.
3Measurement precision
If hierarchical server structure with multiple levels is implemented, then error analysis capability is improved, but communication overhead increases
Solution Approach 1:
The patent assigns different analysis capabilities to different levels of the hierarchical structure: local servers perform immediate error detection and basic analysis with fast response times, while central servers provide comprehensive analysis for complex errors. This local differentiation of quality allows the system to achieve high overall error analysis capability while minimizing communication overhead by handling simple cases locally without requiring central server intervention.
Data Source
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AI summary
A system (100) is provided including at least one monitored device (108) for collecting data for use in detecting an error in the data, a central server (114), and at least one local server (104) communicatively coupled to the at least one monitored device and the central server. The at least one local server is configured to receive the data and an indication of the error detected from the at least one monitored device, determine a solution for use in resolving the error, transmit instructions to perform the solution to the at least one monitored device, and transmit the error and the solution to the central server for storage.