Application-Specific Power Management via Dynamic Interval Adjustment
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Solution Overview
Problem
Conventional power management systems for computing devices do not effectively adjust power settings based on actual user activity and behavior, leading to inefficient energy consumption, as they rely on predetermined inactivity periods that do not account for variations in user interaction patterns.
Innovation Solution
An application-specific power management strategy that uses statistical analysis of user interaction patterns to dynamically adjust power-down intervals for computing device components, such as displays, based on user feedback, to optimize power conservation while minimizing user annoyance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If conventional power management systems use predetermined inactivity periods to control display power-down, then power consumption can be reduced, but user activity variations and behavior patterns are not accounted for, leading to suboptimal power savings
Solution Approach 1:
The system automatically monitors user interactions with applications and autonomously determines optimal power-down intervals without manual configuration. The power management mechanism learns from observed user behavior patterns and self-adjusts timing parameters, eliminating the need for users to manually configure power settings while achieving optimized power savings.
Solution Approach 2:
The power-down interval timing is transformed from a static predetermined value to a dynamic parameter that continuously adapts based on observed user interaction patterns. The system adjusts power management timing in real-time according to application-specific user behavior, enabling the display to remain powered on longer when users are actively working and power down sooner when inactivity is detected.
2Loss of energy
If power management settings are optimized for maximum power savings, then energy consumption is reduced, but user convenience and perceived system responsiveness may deteriorate
Solution Approach 1:
The system continuously monitors user interactions and uses this feedback to dynamically adjust power management timing. By observing when users actually interact with applications and the display, the system learns optimal power-down intervals that balance power savings with user convenience, preventing the display from turning off during active use while maximizing energy savings during genuine inactivity.
Solution Approach 2:
The power-down interval parameter is dynamically changed based on application-specific user behavior patterns. Instead of using a fixed time value, the system adjusts the timing parameter according to observed interactions, allowing the same display to have different power-down intervals depending on which application is active and how users typically interact with it.
Data Source
AI summary
An application-specific power management technique may establish a separate power-down interval for one or more applications based on user interaction with the one or more applications. In some implementations, during use of a particular application, when a management component determines that a period of user inactivity has become greater than or equal to the particular power-down interval established for the particular application, the management component may initiate a power down of one or more components, such as a display.