Adaptive Doze to Hibernate Power Management
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Solution Overview
Problem
Existing power management strategies for mobile computing devices often fail to strike a balance between performance and battery life, leading to user dissatisfaction due to fixed timer-based hibernation transitions that do not adapt to varying battery drain rates or user presence.
Innovation Solution
An adaptive doze to hibernate scheme that monitors battery drain rate and hibernate parameters such as standby budget, minimum standby time, and user presence to dynamically switch between device power states, optimizing power conservation and user experience.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If a fixed timer is used to control device power states, then the device structure is simple, but the adaptability to varying battery drain rates and user presence is poor
Solution Approach 1:
The power management system transitions from static fixed timer-based state control to dynamic adaptation based on real-time battery drain rate monitoring. The system continuously observes drain rate and automatically adjusts power state transitions, making the power management behavior flexible and responsive to changing conditions without requiring complex user configuration.
Solution Approach 2:
The system implements feedback mechanisms by monitoring battery drain rate in real-time and using this information to adjust power state transitions. The drain rate monitoring provides continuous feedback about battery consumption patterns, enabling the system to adapt its behavior accordingly - transitioning to hibernate faster when drain rate is high and maintaining standby longer when drain rate is low.
2Duration of action of moving object
If the device transitions to hibernate mode quickly to conserve power, then battery life is extended, but user experience deteriorates due to longer wake-up times
Solution Approach 1:
The system dynamically adjusts the balance between battery conservation and wake-up speed based on current battery conditions. When battery level is high, the system can afford longer wake-up times and maintains standby state longer. When battery level drops or drain rate increases, the system proactively transitions to hibernate to preserve remaining battery, accepting longer wake-up times as necessary for extending overall battery life.
Solution Approach 2:
The system performs preliminary assessment of battery drain rate and projected battery life before making power state transitions. By monitoring drain rate trends and predicting future battery status, the system can proactively transition to hibernate mode before battery depletion becomes critical, thereby extending usable battery life while managing wake-up time implications.
3Ease of operation
If the device remains in standby mode to maintain quick responsiveness, then user experience is improved, but power consumption increases reducing battery life
Solution Approach 1:
The system dynamically determines the optimal power state by continuously monitoring battery drain rate. When drain rate is low and battery level is sufficient, the system maintains standby mode to preserve quick responsiveness and user experience. When drain rate increases or battery level drops, the system transitions to hibernate to reduce power consumption, accepting reduced responsiveness as a necessary trade-off for battery preservation.
Solution Approach 2:
The system changes the operational parameters of power management based on monitored conditions. By adjusting the threshold parameters for state transitions based on drain rate observations, the system optimizes the balance between responsiveness and power consumption - maintaining more aggressive standby behavior when conditions permit and transitioning to power-saving hibernate when necessary.
4Duration of action of moving object
If power management is aggressive to extend battery life, then battery life is improved, but device performance deteriorates
Solution Approach 1:
The system implements dynamic power management that adapts aggression level based on current battery conditions and usage patterns. Rather than applying fixed aggressive power-saving measures, the system monitors drain rate and adjusts its behavior accordingly - maintaining higher performance states when battery conditions permit and transitioning to aggressive power-saving hibernate mode only when necessary to extend battery life, thereby minimizing performance impact.
Data Source
AI summary
Adaptive doze to hibernate scheme techniques are described for power management of a computing device. Rather than relying upon a fixed timer to control device power states, the adaptive doze to hibernate scheme monitors various hibernate parameters and adapts the hibernation experience in dependence upon the parameters. The hibernate parameters may include but are not limited to a standby budget, minimum standby time, reserve screen on time, and indications of user presence. In operation, a power manager monitors battery drain rate and adaptively determines when to change the device power states of the computing device based on the observed drain rate and the hibernate parameters. The power manager may selectively switch between various states (e.g., high performance, active, wake, standby, hibernate, off, etc.) accordingly.