Adaptive Application Freezing Control for Terminal Devices
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Solution Overview
Problem
Existing freezing control technologies for terminal devices lack flexibility and rationality due to fixed trigger conditions for freezing detection, leading to suboptimal performance and user experience.
Innovation Solution
The method involves dynamically updating the cyclic detection time interval based on the current application running state of the terminal device, allowing for adaptive freezing detection and control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a fixed trigger condition is used for freezing detection, then the freezing control can be implemented, but the flexibility and rationality of freezing control deteriorates
Solution Approach 1:
The patent applies the Dynamics principle by transforming the fixed cyclic detection time interval into a dynamic one that automatically adjusts based on application behavior patterns. The system learns from historical data to identify applications with specific characteristics (such as those that frequently start/stop or consume excessive resources) and adaptively modifies the detection interval for each application, thereby achieving both reliable freezing control and flexible adaptation to different application scenarios.
Solution Approach 2:
The patent implements Parameter changes by modifying the cyclic detection time interval parameter based on learned application behaviors. Instead of using a static parameter, the system dynamically changes this parameter according to the identified behavior patterns of applications, allowing the freezing control mechanism to adapt its sensitivity and response time to match the actual needs of different applications and usage scenarios.
2Productivity
If background applications are controlled to improve performance, then terminal device performance and battery life are improved, but the complexity of control increases
Solution Approach 1:
The patent applies the Self-service principle by implementing an automated learning mechanism that independently analyzes application behaviors and determines freezing strategies without requiring manual user configuration. The system automatically collects data on application startup patterns, resource consumption, and user interactions, then uses this information to autonomously adjust freezing control parameters, thereby improving performance while minimizing the complexity burden on users.
Solution Approach 2:
The patent implements Feedback by establishing a closed-loop control system where the outcomes of freezing actions are continuously monitored and fed back into the learning mechanism. This feedback loop allows the system to refine its understanding of application behaviors and optimize freezing strategies over time, achieving improved terminal performance through an increasingly sophisticated yet automated control process that adapts based on actual system responses.
Data Source
AI summary
An application freezing control method and device, a terminal, and a non-transitory computer-readable storage medium are disclosed. The method may include: updating, after freezing detection processing for currently running applications is triggered based on a current cyclic detection time interval, the cyclic detection time interval in response to determining, based on a current application running state of the terminal device, that the cyclic detection time interval needs to be updated (S101); and determining, based on the updated cyclic detection time interval, whether the freezing detection processing needs to be performed on the currently running applications (S102).