Cross-Domain Fault Correlation for Faster Network Root Cause Analysis
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Solution Overview
Problem
In multi-domain networks, network faults generate a large quantity of fault symptoms and alarm information, leading to low fault diagnosis efficiency due to the need for manual analysis of each single-domain fault by operation and maintenance personnel.
Innovation Solution
A cross-domain fault analysis method and system that analyzes time and service information correlations across multiple domains to identify a single underlying fault cause, reducing the need for individual domain analysis and improving efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual analysis of each single-domain fault is performed by operation and maintenance personnel, then comprehensive fault diagnosis can be achieved, but fault diagnosis efficiency decreases
Solution Approach 1:
The patent introduces a cross-domain fault analysis system as an intermediary between multiple single-domain fault analysis systems. This system collects fault information from different domains, performs correlation analysis on time and service information, and identifies common fault causes across domains, thereby reducing manual analysis workload while maintaining comprehensive diagnosis capability
Solution Approach 2:
The patent merges multiple single-domain fault analysis results into a unified cross-domain fault analysis. By combining fault information from different domains and analyzing their correlations, the system identifies common fault causes that affect multiple domains, reducing redundant analysis while improving overall fault diagnosis efficiency
2Reliability
If a large quantity of fault symptoms and alarm information are processed, then comprehensive fault coverage is achieved, but processing efficiency decreases
Solution Approach 1:
The patent extracts key correlation features from large quantities of fault symptoms and alarm information, specifically focusing on time correlation and service information correlation. By extracting only the most relevant features for cross-domain fault analysis, the system reduces data processing complexity while maintaining comprehensive fault coverage
Solution Approach 2:
The patent changes the analysis parameters from processing individual fault symptoms separately to analyzing correlated parameters across domains. By focusing on time correlation parameters and service information correlation parameters, the system reduces the dimensionality of data processing while achieving comprehensive fault coverage
Data Source
AI summary
Embodiments of this application provide a cross-domain fault analysis method and system. According to the method and the system, whether a first single-domain network fault and a second single-domain network fault are caused by a same fault is determined based on correlation analysis on the first single-domain network fault and the second single-domain network fault in time dimension and service dimension. This resolves a problem of low fault diagnosis efficiency caused by a fact that operation and maintenance personnel needs to analyze each single-domain network fault because the same fault leads to a plurality of single-domain network faults.