Adaptive QoS Parameter Detection in Communication Terminals

The patent applies dynamics by making the QoS parameter detection adaptive rather than static. The terminal device dynamically adjusts which parameters to detect based on current service conditions and user preferences. When service deterioration is detected or user interest is high, more parameters are monitored; under normal conditions, fewer parameters are detected. This dynamic adaptation resolves the contradiction between comprehensive monitoring and resource conservation.

The patent changes the parameters of the monitoring system itself - specifically, the set of detected QoS parameters is changed based on service type, user preferences, and current network conditions. Different parameter sets are selected for different scenarios (e.g., voice service vs. data service, normal operation vs. deterioration). This parameter adaptation allows the system to maintain monitoring effectiveness while reducing overall resource consumption.

The system dynamically adjusts the monitoring intensity based on current terminal performance requirements and service conditions. During normal operation, minimal parameters are detected to preserve terminal performance. When service deterioration is detected or user interest is high, the system temporarily increases monitoring intensity. This dynamic approach ensures that QoS evaluation remains effective while terminal performance is maintained during normal operations.

The patent applies partial action by detecting only the necessary subset of QoS parameters rather than all possible parameters continuously. The system performs full monitoring only when needed (during deterioration or high user interest), and partial monitoring during normal operation. This selective approach maintains sufficient QoS evaluation capability while preserving terminal performance for service execution.

The patent implements periodic monitoring where QoS parameters are detected at specific intervals and under specific conditions rather than continuously. The system periodically checks for service deterioration by monitoring key parameters, and when deterioration is detected or user interest is high, it intensifies monitoring temporarily. This periodic approach maintains reliable deterioration detection while significantly reducing continuous resource consumption compared to constant monitoring.

The system uses feedback from initial parameter detections to control subsequent monitoring intensity. When service quality remains normal, monitoring is reduced to conserve resources. When deterioration is detected or user interest is high, feedback triggers intensified monitoring to ensure reliable detection. This feedback-controlled approach maintains high reliability for deterioration detection while minimizing resource usage during normal operations.