Automated Network Troubleshooting via Parameter-Process Correlation
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Solution Overview
Problem
Troubleshooting processes in the telecommunication industry are time-consuming, especially for edge cases and corner cases where unexpected behavior occurs, and existing methods lack automation for identifying issues.
Innovation Solution
An automated method and device for troubleshooting that determine degraded parameters, identify associated processes, and display problem scenarios, including network malfunctions, using a system that determines if processes were operating during degradation and correlates multiple parameters to identify problem scenarios, with the ability to create new codes for unknown scenarios.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual troubleshooting processes are used, then flexibility in handling diverse network issues is maintained, but troubleshooting time and operational costs increase significantly
Solution Approach 1:
The system enables autonomous self-service troubleshooting by automatically detecting degraded parameters, identifying affected processes, determining problem scenarios, and generating diagnostic information without human intervention. The network management system performs self-diagnosis through automated correlation of parameter degradation with process status and problem scenario databases.
Solution Approach 2:
The patent replaces manual mechanical troubleshooting processes with automated computational systems. Instead of human operators manually analyzing network issues, the system uses automated algorithms to correlate parameter data with process information and problem scenarios, substituting human analytical work with machine-based data processing and pattern recognition.
2Measurement precision
If comprehensive analysis of multiple parameters and processes is performed, then problem scenario identification accuracy improves, but system complexity increases
Solution Approach 1:
The troubleshooting system is segmented into distinct functional modules: a degraded parameter obtaining module, a process identification module, a problem scenario determination module, and an information generation module. Each module handles a specific aspect of the analysis, breaking down the complex overall task into manageable segments that can be processed independently and systematically.
Solution Approach 2:
The system introduces an intermediary problem scenario database that stores pre-defined problem scenarios and their associated parameter-process relationships. This intermediary structure mediates between the raw parameter data and the final diagnosis, providing a structured framework that simplifies the correlation process while maintaining high identification accuracy.
3Productivity
If automated troubleshooting systems are implemented, then troubleshooting speed and operational efficiency improve, but the ability to handle unexpected edge cases and corner cases decreases
Solution Approach 1:
The system dynamically adapts to different troubleshooting scenarios by flexibly correlating degraded parameters with currently operating processes and matching them against stored problem scenarios. The automated analysis adjusts to various edge cases and corner cases by evaluating real-time process status and parameter relationships, enabling versatile handling of unexpected situations while maintaining automated efficiency.
Data Source
AI summary
A method of automatic troubleshooting, includes determining that a first parameter was degraded; identifying at least one first process corresponding to the first parameter; determining whether the at least one first process was operating while the first parameter was degraded; based on determining that the at least one first process was operating while the first parameter was degraded, identifying a problem scenario corresponding to the first parameter and the at least one first process; identifying a plurality of second parameters associated with the problem scenario; determining whether the plurality of second parameters were degraded; based on determining that the plurality of second parameters were degraded, determining that the problem scenario occurred; and based on determining that the problem scenario occurred, displaying information indicating the problem scenario.