Mobile Device Power State Control via Subsystem Feature Extraction
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Solution Overview
Problem
Mobile devices face challenges in determining and setting the power state of shared resources like CPUs to efficiently serve various subsystems while preserving battery life, as each subsystem has different workloads and performance specifications.
Innovation Solution
A method involving a processor that extracts features from multiple subsystems, determines parameters based on these features, and operates shared resources such as CPUs to optimize power consumption and performance using reinforcement learning and deep learning architectures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If the power state of shared resources is set to serve various subsystems with different workloads and performance specifications, then device performance is improved, but battery consumption increases
Solution Approach 1:
The system dynamically adjusts the power state of shared resources based on real-time workload characteristics and performance requirements of active subsystems. The processor monitors subsystem demands and modifies operating parameters (frequency, voltage, power state) of shared resources adaptively, transitioning between high-performance and low-power states as needed to match actual computational demands.
Solution Approach 2:
The invention changes operational parameters of shared resources (such as CPU frequency, voltage levels, and power states) based on extracted features from subsystem workloads. By adjusting these parameters dynamically rather than maintaining fixed high-performance settings, the system achieves optimal balance between performance delivery and power consumption reduction.
2Use of energy by moving object
If the power state of shared resources is optimized for battery preservation, then energy consumption is reduced, but device performance deteriorates
Solution Approach 1:
The system implements feedback mechanisms where the processor continuously monitors subsystem workload characteristics, performance specifications, and power consumption metrics. Based on this feedback, the system adjusts the power state of shared resources to maintain adequate performance while minimizing energy consumption, creating a closed-loop control system that adapts to changing operational conditions.
Solution Approach 2:
The system applies partial action by providing just enough processing power to meet subsystem requirements rather than continuously allocating maximum resources. The processor extracts features from workload characteristics and determines the minimum necessary power state to satisfy performance specifications, avoiding excessive resource allocation that would waste energy.
3Adaptability or versatility
If multiple subsystems with different workloads operate simultaneously using shared resources, then system functionality is enhanced, but power state determination becomes complex
Solution Approach 1:
The system segments the power management task by extracting specific features from each subsystem's workload characteristics and treating them as distinct input parameters. The processor analyzes workload features from multiple subsystems separately and combines this information to determine appropriate power states for shared resources, breaking down the complex multi-subsystem problem into manageable feature-extraction and decision-making stages.
Solution Approach 2:
The invention introduces an intermediary layer of workload feature extraction and analysis between the diverse subsystems and the shared resource power state control. This intermediary processor layer translates various subsystem requirements into standardized workload features, simplifying the determination of appropriate power states for shared resources despite the diversity of subsystem demands.
Data Source
AI summary
A method of operating a shared resource in a mobile device includes extracting a set of features from a plurality of subsystems of the mobile device. The set of features may be extracted from each subsystem of the plurality of subsystems requesting services from one or more shared resources of the mobile device. One or more parameter of the shared resource(s) may be determined based on the extracted set of features from the plurality of subsystems. The shared resource(s) may be operated based on the determined parameter(s).