Control-Message Analysis for Communication Abnormality Detection
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Solution Overview
Problem
In communication systems with autonomous distributed communication apparatuses, network orchestrators lack comprehensive information for effective abnormality detection and causal analysis.
Innovation Solution
An analysis method and system that acquire control messages, generate metrics and event data from these messages, and utilize a learning model to detect and identify abnormalities in the communication system.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If control messages are acquired and processed to generate metrics data and event data, then abnormality detection capability is improved, but system complexity increases
Solution Approach 1:
The system segments the processing of control messages into distinct functional components: message acquisition, metrics data generation, event data generation, and abnormality detection. Each component handles specific aspects of data processing independently, making the complex system more manageable and maintainable while improving detection capability through specialized processing at each stage.
Solution Approach 2:
The patent introduces intermediary data structures (metrics data and event data) that mediate between the raw control messages and the final abnormality detection. These intermediaries transform and organize the raw message data into meaningful statistical information and historical records, enabling complex detection algorithms to operate on structured data rather than raw messages, thus improving detection capability while isolating complexity in well-defined transformation layers.
2Measurement precision
If detailed information is collected from control messages, then abnormality detection precision is improved, but information processing load increases
Solution Approach 1:
The system extracts only the necessary information from control messages to generate metrics data (statistical summaries) and event data (historical records). By selectively extracting and transforming only the relevant fields and patterns from the raw messages, the system achieves high detection precision for abnormalities while minimizing the processing load by avoiding unnecessary analysis of all message contents.
Solution Approach 2:
The patent performs preliminary processing of control messages by pre-generating metrics data and event data in a structured format before actual abnormality detection occurs. This preliminary action organizes and pre-processes the information, so that when abnormality detection runs, it operates on already-organized data rather than raw messages, reducing the computational load during detection while maintaining high precision through the pre-computed statistical and historical information.
Data Source
AI summary
To achieve an analysis system that enables a suitable abnormality detection by acquiring information required for detecting abnormality in a communication system. An analysis system carries out: a process of acquiring control messages exchanged between a plurality of communication apparatuses included in a communication system; a process of generating metrics data which is statistical information, for each of the types of the control messages, on the basis of the control messages; a process of generating event data which is history data on the control messages on the basis of the control message; and a process of detecting occurrence of abnormality in the communication system on the basis of the metrics data and the event data.