Restore Time Predictor for Asymmetric Multiprocessor Power Management
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Solution Overview
Problem
Mobile devices face challenges in accurately determining the restore time to transition from a low-power mode to an active mode to process regularly scheduled signals, leading to potential data loss or unnecessary power consumption.
Innovation Solution
A mobile device with a restore time determination function and state detection function that determines and stores restore times for various operating states, using a matrix to predict the time required to move the processor from a low-power mode to an active mode, ensuring timely processing of signals while minimizing power consumption.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If the processor enters low-power mode to save energy, then power consumption is reduced, but the restore time to active mode increases and may cause missed signals
Solution Approach 1:
The system performs preliminary actions by determining and storing restore times for different operating states before actually needing to wake up. When in low-power mode, the processor can quickly retrieve the pre-calculated restore time for its current state and wake up at the precise moment needed, rather than using conservative estimates that would require earlier wake-up times.
Solution Approach 2:
The system makes the restore time dynamic by determining different restore times based on the specific operating state of the processor. Instead of using a fixed, conservative restore time, the system adapts the restore time according to the current state (e.g., different states have different wake-up requirements), allowing optimization for each specific condition.
2Reliability
If the processor wakes up early to ensure signal reception, then signal reception reliability is improved, but power consumption increases due to extended active period
Solution Approach 1:
The system performs preliminary calculations of restore times for all possible operating states and stores them in memory. This allows the processor to wake up at the precise moment needed rather than using conservative early wake-up times, thereby maintaining reliability while minimizing the active period and power consumption.
Solution Approach 2:
The system changes the parameter of restore time based on the operating state. By determining and storing specific restore times for different states (e.g., different CPU frequencies, different radio states), the system can precisely control the wake-up timing to match the actual requirements of each state, avoiding both early wake-ups (wasting power) and late wake-ups (missing signals).
3Loss of time
If the processor remains in active mode to avoid restore latency, then signal processing timeliness is improved, but power consumption increases during idle periods
Solution Approach 1:
The system performs preliminary determination and storage of restore times for different operating states. This allows the processor to confidently enter low-power mode knowing the exact restore time required for its current state, eliminating the need to remain in active mode to avoid latency uncertainty, thereby reducing power consumption during idle periods while maintaining timeliness.
4Device complexity
If the system uses a fixed restore time estimate, then system complexity is reduced, but measurement precision of actual restore time deteriorates
Solution Approach 1:
The system segments the restore time determination by creating separate restore time values for different operating states. Instead of using a single fixed estimate, the system divides the problem into multiple state-specific restore times (e.g., different states for CPU frequency, radio state, memory state), improving precision while keeping each individual segment simple to manage.
Solution Approach 2:
The system creates a universal solution by determining restore times for multiple different operating states and storing them in a lookup table. This multi-functional approach allows the same mechanism (retrieve and use stored restore time) to work accurately across all different processor states, improving precision without significantly increasing complexity.
Data Source
AI summary
In an aspect there is provided a method of moving a processor of a mobile device from a low-power state for conserving power to an active mode for processing signals. The mobile device is configured to receive regularly scheduled signals. The method comprises, for each of multiple operating states of the mobile device determining a restore time associated with the operating state of the mobile device and storing each determined restore time in association with its operating state. The method further comprises detecting a current operating state of the mobile device and using the determined restore time for that state to set a trigger time to control movement of the processor of the mobile device to enter the active mode from the low-power mode in time to process the scheduled signals.