Adaptive Power Manager for Information Handling Systems
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Solution Overview
Problem
Existing power management systems in information handling systems, such as those using ACPI, often lead to inconvenient delays in resuming from reduced power states, causing end users to disable automated power-saving features due to the mismatch between default power state transitions and user behavior.
Innovation Solution
A power manager that adapts power state transitions based on user preferences and behavior, prioritizing faster resume times during active periods by enforcing the S3 standby mode instead of S4 hibernate mode during specified times, and transitioning to S4 mode during inactive periods to conserve power.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the system transitions to S4 hibernate mode to reduce power consumption, then power savings increase, but resume time increases
Solution Approach 1:
The system dynamically adjusts the power state transition behavior based on learned user patterns. The power manager monitors user activity and automatically modifies transition timing and state selection to balance power savings with resume speed according to real-time user needs, making the power management strategy adaptive rather than static.
Solution Approach 2:
The system performs preliminary actions by transitioning to S3 standby mode before the predicted resume time arrives. This preemptive transition ensures that when the user actually resumes, the system is already in a faster-ready state, thus reducing perceived resume time while still maintaining power efficiency through the intermediate S3 state.
2Loss of energy
If automated power state transitions are enforced, then power consumption decreases, but user convenience decreases
Solution Approach 1:
The power manager implements feedback mechanisms by continuously monitoring user activity patterns and system usage. This feedback loop allows the system to learn from user behavior and automatically adjust power state transitions, eliminating the need for users to manually configure or disable power management features while still providing convenient, personalized power saving behavior.
Solution Approach 2:
The system provides self-service power management by automatically monitoring user behavior and adjusting power state transitions without user intervention. The power manager autonomously determines optimal transition times and states based on learned patterns, making the system convenient to use while achieving power savings without requiring user configuration or awareness.
3Loss of time
If the system transitions to S3 standby mode, then resume time decreases, but power consumption increases
Solution Approach 1:
The system uses periodic user activity analysis to determine optimal power state transitions. By monitoring user behavior patterns over time and applying periodic adjustments based on these patterns, the system intelligently selects between S3 and S4 states, achieving fast resume when needed while maintaining power efficiency during extended idle periods.
Data Source
AI summary
Information handling system power management in standby and hibernate states is adapted to reduce transition times for end user requests to resume to an operational state. During fast resume time periods, transitions to the hibernate state are limited so that recovery to an operational states has the reduced resume time associated with the standby state. The fast resume time periods are set by user preference or automatically set by monitoring end user interactions with the information handling system to predict fast resume times appropriate for the end user. In one embodiment, a power manager automatically transitions the information handling system from the hibernate state to a standby state a predetermined time period before a fast resume period begins.