Adaptive Application Performance Controller for Mobile Devices
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Solution Overview
Problem
Mobile device applications typically run at a single performance level regardless of user recharge habits, failing to adapt to varying energy availability.
Innovation Solution
A method and apparatus for adaptive application performance that monitors battery recharging habits to adjust application performance levels based on available energy, using a controller to determine and implement performance measures such as minimum, increased, or full performance depending on charge level and recharging frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If applications run at a single performance level, then device operation is simple and stable, but energy efficiency is poor and performance cannot be optimized for different charging habits
Solution Approach 1:
The patent implements dynamic performance adjustment by transitioning from a static single performance level to multiple adaptive performance levels (minimum, increased, full) based on real-time charging state detection. The controller dynamically switches between performance modes according to charging frequency and charge level, optimizing energy efficiency while maintaining productivity.
Solution Approach 2:
The system changes operational parameters by adjusting application performance levels based on detected charging parameters. When charging frequency is high and charge level is high, the system transitions to full performance mode; when charging is infrequent or charge level is low, it transitions to minimum or increased performance mode, thereby optimizing energy consumption relative to productivity.
2Use of energy by moving object
If applications adapt performance to charging habits, then energy efficiency improves, but system complexity increases
Solution Approach 1:
The patent segments the performance control into distinct levels (minimum, increased, full) and separates the detection function from the control function. The controller detects charging parameters independently and then selects appropriate performance levels, simplifying the overall system architecture while achieving energy efficiency improvements.
Solution Approach 2:
The system implements self-service by automatically detecting charging habits and autonomously adjusting performance levels without user intervention. The controller monitors charging parameters and automatically transitions between performance modes, reducing the need for complex user interfaces or manual configuration while improving energy efficiency.
3Productivity
If performance is optimized for frequent chargers, then productivity increases for this group, but users with different habits experience suboptimal performance
Solution Approach 1:
The system dynamically adapts to different user charging habits by continuously monitoring charging frequency and charge levels. Rather than being optimized for a single user type, the controller adjusts performance levels in real-time based on detected charging patterns, ensuring optimal productivity for both frequent and infrequent chargers through adaptive behavior.
Solution Approach 2:
The patent implements a universal performance control system that serves multiple user types through a single adaptive mechanism. The controller handles different charging scenarios (frequent charging, infrequent charging, high charge levels, low charge levels) using the same detection and adjustment framework, making the system versatile across different user habits while maintaining high productivity for all users.
Data Source
AI summary
A method and apparatus of adaptive application performance includes a determination of at least one criteria for implementing adaptive application performance measures. Based upon the determination, adaptive application performance measures are implemented.