Controller Network Anomaly Diagnosis Using Event Logs and Statistics
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Solution Overview
Problem
Identifying the cause of communication errors in complex networked controller systems has become increasingly difficult due to network complications.
Innovation Solution
A control system and anomaly factor estimation program that utilizes an information processing apparatus to analyze event logs, access logs, and network statistical information to provide an interactive user interface for easily identifying the factors causing anomalies in a network-connected controller system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a large-scale networked system is adopted to improve controller performance and functionality, then system capability increases, but difficulty in identifying communication error causes increases
Solution Approach 1:
The patent segments the complex network error identification process into distinct components: event log analysis, access log analysis, and network statistical information analysis. Each component handles a specific aspect of error detection, making the overall complex system manageable through modular analysis of individual error sources and types.
Solution Approach 2:
The patent introduces an intermediary diagnostic system that mediates between the complex network infrastructure and the user. This intermediary automatically collects and analyzes data from multiple sources (event logs, access logs, network statistics) and presents synthesized diagnostic information, shielding users from the underlying network complexity while maintaining high diagnostic capability.
2Measurement precision
If comprehensive network monitoring is implemented to identify error causes, then diagnostic capability improves, but system complexity increases
Solution Approach 1:
The patent merges multiple data sources (event logs, access logs, network statistical information) and multiple analysis functions into a single integrated diagnostic system. This consolidation provides comprehensive diagnostic capability while avoiding the complexity of managing separate monitoring tools, as the system unifiedly processes all network data through one interface.
Solution Approach 2:
The diagnostic system performs self-service by automatically collecting data from network components, analyzing logs and statistics, and generating diagnostic conclusions without requiring manual intervention. This automation enhances diagnostic precision while reducing the operational complexity for users, as the system independently manages the complex analysis tasks.
3Productivity
If automated factor identification is implemented, then identification speed improves, but automation extent increases
Solution Approach 1:
The system performs preliminary actions by pre-collecting and organizing network data (event logs, access logs, statistical information) and pre-analyzing potential error patterns before actual errors occur. This preparation enables rapid automated identification when errors happen, achieving high identification speed while the automation is already in place to handle the analysis.
Solution Approach 2:
The patent implements feedback mechanisms where the automated diagnostic system continuously monitors network performance, compares actual behavior against expected patterns, and adjusts its analysis based on observed anomalies. This feedback loop enables the automation to learn from past errors and improve identification accuracy over time, maintaining high productivity while refining the automation's diagnostic capabilities.
Data Source
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AI summary
A control system which controls a control target includes a controller connected to one or more devices through a network, and an information processing apparatus connected to the controller. The controller includes an event log containing an event having occurred during a control operation, and network statistical information containing statistical information associated with data transmission on the network. The information processing apparatus includes a factor estimation unit that provides an interactive user interface in accordance with selection of an anomaly phenomenon registered in the event log.