Automated Fault Recovery for Network Topology Analysis
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Solution Overview
Problem
The increasing scale of networks leads to a high volume of alarms, making it difficult for operation and maintenance personnel to identify faults efficiently, resulting in prolonged mean time to diagnose (MTTD) and low efficiency in network fault recovery.
Innovation Solution
A method and apparatus for automatic fault recovery that involves obtaining network composition and abnormal event information, using models to determine the possible root cause of faults, and generating corresponding fault recovery plans, thereby improving accuracy and efficiency of fault detection and recovery.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual alarm monitoring and fault diagnosis is performed by operation and maintenance personnel, then human expertise and judgment can be applied to identify faults, but the mean time to diagnose (MTTD) increases and efficiency of network fault recovery decreases due to the overwhelming volume of alarms
Solution Approach 1:
The patent replaces manual mechanical analysis of alarms by operation and maintenance personnel with an automated electronic system comprising a collecting module, processing module, and analyzing module. This electronic system automatically collects alarm information, processes it through predefined rules and algorithms, and generates fault location results, thereby eliminating the time-consuming manual diagnosis process while maintaining or improving identification accuracy.
Solution Approach 2:
The system enables self-service fault diagnosis by automatically collecting alarm data from network devices, processing the information through embedded rules and algorithms, and generating fault location results without requiring continuous human intervention. The automated processing module independently analyzes alarm patterns and identifies root causes, allowing the system to serve itself in diagnosing faults.
2Reliability
If manual fault diagnosis and recovery planning is performed, then customized recovery measures can be selected based on expert experience, but the process consumes large amounts of time and workforce
Solution Approach 1:
The patent replaces manual fault recovery planning with an automated electronic system that collects alarm information, processes it through predefined rules and algorithms, and automatically generates fault location results and recovery recommendations. This substitution eliminates the time-consuming manual processes of fault diagnosis and recovery planning while maintaining reliability through structured analysis methods.
Solution Approach 2:
The system performs preliminary action by pre-configuring processing rules and algorithms in the processing module that enable automatic fault analysis and recovery planning. These predefined rules are established in advance to handle various fault scenarios, allowing the system to quickly generate recovery recommendations without requiring real-time human expert intervention for each fault event.
3Measurement precision
If comprehensive network composition information and abnormal event information are collected and analyzed using models, then the accuracy and efficiency of fault root cause identification is greatly improved, but the device complexity and information processing requirements increase
Solution Approach 1:
The patent divides the complex fault diagnosis system into distinct functional modules: a collecting module for gathering alarm information, a processing module for analyzing the data using predefined rules and algorithms, and an analyzing module for generating fault location results. This segmentation reduces system complexity by organizing functions into manageable, independent components while maintaining high identification accuracy through comprehensive information processing.
Data Source
AI summary
A fault recovery method and apparatus, and a storage medium are provided, and belong to the field of Internet technologies. In the method, network composition information and abnormal event information of a target network are obtained, where the network composition information includes a network topology of the target network and device information of a plurality of network devices on the target network, and the device information includes one or more of interface configuration information, protocol configuration information, and service configuration information; and then a possible root cause of a fault of the target network is determined based on the network composition information and the abnormal event information, where the possible root cause of the fault is used to determine a corresponding fault recovery plan.