Mobile App Power Consumption Detection Using Multi-Dimensional Thresholds
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Solution Overview
Problem
Existing methods for detecting power consumption of applications in smart mobile terminals cannot effectively identify abnormal power usage, as they solely rely on the amount of power consumption without considering other factors like wake-up times and CPU utilization.
Innovation Solution
A method and device that detect power consumption by monitoring wake-up times, wake-lock time duration, and CPU utilization during screen-off periods, prompting abnormal power consumption if any of these parameters exceed predefined threshold values.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If power consumption detection is based solely on the amount of power consumption, then the detection method is simple, but the detection accuracy is low and cannot identify abnormal power usage
Solution Approach 1:
The patent segments the power consumption detection into multiple dimensions: wake-up times, wake-lock time duration, and CPU utilization. Each dimension is detected and evaluated separately against threshold values, allowing comprehensive analysis of abnormal power usage without requiring a single complex detection mechanism.
Solution Approach 2:
The patent transitions from one-dimensional power consumption amount detection to multi-dimensional detection by incorporating wake-up times, wake-lock duration, and CPU utilization. This dimensional expansion enables more accurate identification of abnormal power usage patterns while maintaining manageable system complexity through modular detection of each parameter.
2Measurement precision
If multiple parameters (wakeup times, wake-lock time, CPU utilization) are monitored, then the detection accuracy improves, but the detection process becomes more complex
Solution Approach 1:
The detection process is segmented into three independent parameter detections: wake-up times counting, wake-lock time duration measurement, and CPU utilization monitoring. Each parameter is detected and evaluated against its own threshold independently, simplifying the overall detection process while improving accuracy through multi-parameter analysis.
Solution Approach 2:
The patent changes the detection parameters from单一的power consumption amount to multiple parameters (wakeup times, wake-lock time, CPU utilization). Each parameter has its own threshold value for comparison, enabling more precise identification of abnormal power usage while keeping the detection logic straightforward through parameter-based threshold evaluation.
3Reliability
If screen-off duration monitoring is implemented with preset thresholds, then false positives are reduced, but the detection time increases
Solution Approach 1:
The system performs preliminary actions by setting preset threshold values for screen-off duration before actual detection occurs. These pre-configured thresholds enable quick comparison and decision-making during detection, reducing the time required for analysis while maintaining high reliability through predetermined criteria for identifying abnormal power consumption.
Data Source
AI summary
Provided is a method for detecting power consumption of an application, including following steps: when a screen of a mobile terminal is turned on, detecting wakeup times, wake-lock time duration and CPU utilization of applications in the time duration of screen-off by a device for detecting power consumption of an application; prompting that power consumption of an application is abnormal by said device when said application satisfies at least one of following conditions: wakeup tunes reach a first threshold value; wake-lock time duration reaches a second threshold value; CPU utilization reaches a third threshold value. The method provided in the present disclosure is capable of detecting whether power consumption of an application is abnormal. In addition, the present disclosure further provides a device and a computer storage medium for detecting power consumption of an application.