Predictive Network Switching for Stable Mobile Connectivity
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Solution Overview
Problem
Mobile devices often experience poor internet connectivity or loss of connection due to late or premature switching between available networks, such as WiFi and cellular networks, leading to degraded performance or complete disconnection.
Innovation Solution
A mobile device equipped with quality of connection logic, RSSI change logic, and switch network logic proactively predicts network degradation by analyzing signal strength and velocity, allowing it to switch to a new network before connectivity issues arise, using algorithms like Kalman Filters to refine predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the device switches to a second network connection when the first connection falters, then network connectivity is maintained, but the switching may occur too late causing poor internet connection or complete disconnection
Solution Approach 1:
The system performs preliminary actions by proactively scanning for alternative networks and predicting future connection quality based on current signal strength trends. This allows the device to switch networks before the current connection completely fails, preventing connectivity loss rather than reacting after failure occurs.
Solution Approach 2:
The system continuously monitors signal strength and uses this feedback to predict future connection quality. By analyzing the rate of change in signal strength, the system can anticipate when connection quality will deteriorate below acceptable thresholds and trigger a network switch in advance, optimizing the timing of the transition.
2Reliability
If the device switches to a second network connection too early, then connectivity is maintained, but thrashing between network types occurs causing degraded performance
Solution Approach 1:
The system uses continuous feedback from signal strength monitoring to make informed switching decisions. By analyzing trends and predicting future quality, the system only triggers a network switch when prediction indicates actual deterioration will occur, avoiding premature switches that would cause thrashing and performance degradation.
Solution Approach 2:
The system changes the parameter of network switching from a reactive threshold-based approach to a predictive approach using signal strength trends and velocity. This allows the system to optimize the switching parameter timing, switching neither too early nor too late, but at the optimal moment predicted by the analysis of signal characteristics.
3Reliability
If the device monitors network signal strength continuously, then connection quality is maintained, but energy consumption increases
Solution Approach 1:
The system performs preliminary network scanning and quality assessment only when signal strength trends indicate potential deterioration. Instead of continuous monitoring, the system proactively checks alternative networks when prediction algorithms suggest the current connection may soon become inadequate, reducing unnecessary energy consumption while maintaining connectivity.
Solution Approach 2:
The system applies partial monitoring by focusing computational resources on analyzing signal strength trends and predicting future quality only when necessary. Rather than continuously scanning all available networks at full intensity, the system performs targeted predictions and scans based on current connection conditions, reducing energy usage while maintaining effective monitoring.
Data Source
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AI summary
A method (500) for switching between network connections for a mobile device (102) includes determining, by the mobile device, a quality of connection corresponding to a first network (104) provided by an access point (106) and determining, by the mobile device, a rate of change of a received signal strength indication (RSSI) corresponding to the first network. The method also includes determining, by the mobile device, a quality score based on the quality of connection and the rate of change of the RSSI. The method further includes switching, by the mobile device, from the first network to a second network (116) based on a result of comparing the quality score to a quality score threshold.