Fault Propagation Path Analysis With Incremental Historical Updates
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional methods for determining fault propagation paths in networks require processing all historical and newly generated network data, leading to low calculation efficiency and high storage costs.
Innovation Solution
A data processing method that stores only historical fault propagation paths, updating them incrementally, and uses a frequent subgraph mining algorithm to analyze network data, allowing for efficient and scalable fault localization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If all historical network data and newly generated network data are processed to determine fault propagation paths, then comprehensive fault analysis is achieved, but calculation efficiency deteriorates and storage costs increase
Solution Approach 1:
The patent extracts only the essential fault propagation path information from historical network data, storing condensed representations rather than complete raw datasets. This extraction principle allows comprehensive fault analysis to be performed on condensed data, maintaining accuracy while reducing computational burden and storage requirements
Solution Approach 2:
The patent performs preliminary processing of historical network data to pre-calculate and store fault propagation paths before they are needed for new fault analysis. By pre-processing and condensing historical data into essential propagation path representations, the system avoids reprocessing large volumes of raw historical data when new faults occur, thereby improving calculation efficiency
2Reliability
If all historical network data is stored for fault propagation path determination, then complete fault history is preserved, but storage costs increase
Solution Approach 1:
The patent extracts only the essential fault propagation path information from historical network data, storing condensed representations rather than complete raw datasets. This extraction principle allows comprehensive fault analysis to be performed on condensed data, maintaining accuracy while reducing computational burden and storage requirements
Solution Approach 2:
The patent transforms the representation parameters of historical data by converting detailed network data into condensed fault propagation path representations. This parameter change maintains the essential fault history information needed for reliability analysis while dramatically reducing the quantity of stored data, thereby lowering storage costs
3Measurement precision
If all network data is reprocessed each time a fault propagation path is needed, then up-to-date analysis is achieved, but time consumption increases
Solution Approach 1:
The patent performs preliminary processing of historical network data to pre-calculate and store fault propagation paths before they are needed for new fault analysis. By pre-processing and condensing historical data into essential propagation path representations, the system avoids reprocessing large volumes of raw historical data when new faults occur, thereby improving calculation efficiency
Solution Approach 2:
The patent implements a dynamic approach where the system maintains condensed fault propagation path information that can be quickly updated and queried. Rather than statically storing and reprocessing all raw historical data, the dynamic condensed representations enable rapid fault analysis while maintaining accuracy through selective updates
Data Source
AI summary
A data processing method where an analysis device obtains first network data and historical fault propagation paths and processes the first network data to obtain a first fault propagation path. When the historical fault propagation paths include a target fault propagation path that is the same as the first fault propagation path, the analysis device updates a quantity of target fault propagation paths.