Cell Network Anomaly Prediction for Proactive Recovery
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Solution Overview
Problem
Existing network anomaly handling methods in mobile networks result in discontinuity of network usage due to delayed response to network anomalies, affecting user experience, especially in areas with frequent network issues.
Innovation Solution
A method where an electronic device sends cell and operator information to a server, receives an anomaly list with predicted network recovery strategies, and executes these strategies proactively to prevent network disruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If network anomaly handling is performed after anomaly detection, then network usage continuity is maintained, but user experience deteriorates due to delayed response and disruptions
Solution Approach 1:
The system performs preliminary actions by predicting network anomalies before they occur and executing recovery strategies in advance. The electronic device receives anomaly prediction information from the server and proactively executes recovery strategies (such as switching to alternative networks or adjusting connection parameters) before the actual anomaly occurs, thereby maintaining continuous network usage and improving user experience by eliminating disruptions rather than responding to them after occurrence.
2Reliability
If real-time network monitoring and prediction is implemented, then network anomaly response is improved, but device complexity increases
Solution Approach 1:
The server acts as an intermediary that performs complex network monitoring, data analysis, and anomaly prediction functions remotely. The electronic device simply sends its identifier to the server and receives prediction results and recovery strategies. This intermediary approach allows real-time network monitoring and prediction to be implemented without significantly increasing the complexity of the electronic device itself, as the computational burden is shifted to the server.
Solution Approach 2:
The server provides multi-functional services including network monitoring, anomaly prediction, and recovery strategy generation for multiple electronic devices simultaneously. This universal approach consolidates complex functions into a single system that serves multiple clients, reducing the complexity burden on individual devices while maintaining reliable real-time network anomaly response.
3Reliability
If proactive recovery strategies are executed, then network disruption is minimized, but information processing requirements increase
Solution Approach 1:
The system extracts only the essential information needed for anomaly prediction and recovery from the vast amount of network data. Instead of processing all network traffic details locally, the electronic device sends minimal identifier information to the server, which extracts and analyzes only the necessary patterns to generate predictions and recovery strategies. This extraction approach reduces information processing requirements at the device level while maintaining effective anomaly response.
Data Source
AI summary
A network anomaly recovery method, which includes sending a target data packet to a server when the first electronic device uses a network of a first cell; receiving a first cell anomaly list sent by the server, where the first cell anomaly list includes N anomaly time periods and a network recovery strategy corresponding to each anomaly time period, where the N anomaly time periods are time periods in which a network anomaly occurs when a second electronic device uses the network of the first cell; predicting, according to the first cell anomaly list, that a network anomaly occurs on the first electronic device in a target time period; and executing, when a system moment of the first electronic device is in the target time period, a target network recovery strategy corresponding to the target time period.