Samsung electronics co., ltd. (20240333615). NETWORK ANALYSIS USING DATASET SHIFT DETECTION simplified abstract
Contents
NETWORK ANALYSIS USING DATASET SHIFT DETECTION
Organization Name
Inventor(s)
Russell Ford of Campbell CA (US)
NETWORK ANALYSIS USING DATASET SHIFT DETECTION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240333615 titled 'NETWORK ANALYSIS USING DATASET SHIFT DETECTION
Simplified Explanation: The patent application describes methods and apparatuses for automating configuration management in cellular networks using correlation analysis and anomaly detection.
- Assigning contexts to different time intervals of data based on correlation analysis of historic time-series data.
- Grouping historic time-series data based on the assigned contexts.
- Identifying anomalies by computing anomaly scores comparing new data with grouped historic time-series data.
- Indicating an anomaly event when the computed anomaly score exceeds a threshold.
- Computing an aggregate anomaly score for context-based multivariate anomaly detection.
Key Features and Innovation: - Automation of configuration management in cellular networks. - Correlation analysis for assigning contexts to data. - Anomaly detection using historic time-series data. - Threshold-based anomaly event indication. - Aggregate anomaly score computation for multivariate anomaly detection.
Potential Applications: This technology can be applied in: - Telecommunications industry for network management. - IoT devices for anomaly detection. - Data analytics for pattern recognition.
Problems Solved: - Manual configuration management in cellular networks. - Difficulty in detecting anomalies in large datasets. - Lack of automated tools for context-based anomaly detection.
Benefits: - Improved efficiency in network configuration management. - Enhanced anomaly detection capabilities. - Reduction in manual intervention for network monitoring.
Commercial Applications: Automated configuration management in cellular networks can revolutionize network operations, leading to improved performance, reduced downtime, and enhanced security measures in the telecommunications industry.
Questions about Configuration Management in Cellular Networks: 1. How does correlation analysis help in assigning contexts to data for anomaly detection? 2. What are the potential benefits of automating configuration management in cellular networks?
Original Abstract Submitted
methods and apparatuses for automating configuration management in cellular networks. a method of a computing device comprises: assigning, based on a correlation analysis, contexts to different time intervals of data, wherein the correlation analysis is performed based on historic time-series data; grouping, based on the assigned contexts, the historic time-series data; identifying context and compute an anomaly score comparing new data and the grouped historic-time series data of the context; indicating an event of anomaly based on a determination that the computed anomaly score exceeds a first threshold that is identified based on a function of per-context data; and computing, based on the event of the anomaly, an aggregate anomaly score or indicate using a value of mean or moving average of a set of latest anomaly scores, for a context-based multivariate anomaly detection.
