Adaptive Computer Reconfiguration Using Usage Telemetry
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Solution Overview
Problem
Existing electronic devices face challenges in optimizing system configurations due to varying user needs and hardware conditions, leading to sub-optimal performance and user experience, as current methods often rely on static or noisy adaptive algorithms that fail to consider long-term usage patterns and hardware degradation.
Innovation Solution
Implementing a 'slow' and 'personal' adaption-based configuration solution that monitors user usage telemetry and system hardware conditions, allowing the computer system to self-adapt by adjusting system tunables, policies, and algorithms to enhance power, performance, and responsiveness.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If static configuration methods are used, then device complexity is reduced, but performance optimization and adaptability to varying user needs deteriorate
Solution Approach 1:
The patent implements dynamic reconfiguration of the computer system by continuously monitoring usage telemetry data and automatically adjusting system tunables, policies, and algorithms based on detected usage patterns. This transforms the static configuration into a dynamic system that adapts to varying user needs and hardware conditions, resolving the contradiction between configuration adaptability and system complexity through automated adaptive mechanisms.
Solution Approach 2:
The system performs self-configuration by autonomously analyzing its own usage telemetry data and automatically adjusting its configuration parameters without requiring external intervention. This self-service approach enables the system to optimize its own performance while managing the complexity internally, allowing high adaptability without proportionally increasing user-facing complexity.
2Speed
If noisy adaptive algorithms are used, then responsiveness is improved, but reliability and consistency of performance deteriorate
Solution Approach 1:
The system performs preliminary analysis of usage telemetry data to detect stable usage patterns before making configuration adjustments. By requiring pattern detection over time rather than immediate reaction to single events, the system filters out noise while maintaining responsiveness to genuine usage changes, thus improving performance consistency without sacrificing adaptability.
Solution Approach 2:
The system implements continuous feedback loops where configuration changes are monitored and evaluated against actual performance outcomes. This feedback mechanism allows the system to learn from previous adjustments and refine its adaptive behavior, ensuring that responsiveness is maintained while reliability improves through data-driven decision making.
3Ease of operation
If frequent configuration adjustments are made, then user experience is improved, but energy consumption and system stability worsen
Solution Approach 1:
The system implements periodic monitoring and analysis of usage telemetry data rather than continuous real-time adjustments. Configuration changes are made only when stable usage patterns are detected over defined time periods, reducing the frequency of adjustments while maintaining user experience quality. This periodic approach lowers energy consumption and system instability risks associated with frequent reconfiguration.
4Productivity
If static configuration is used, then manufacturing precision is maintained, but productivity and performance optimization deteriorate
Solution Approach 1:
The system maintains a standardized base configuration that can be universally applied across devices, ensuring manufacturing precision and consistency. Layered on top of this universal base is an adaptive configuration layer that automatically adjusts parameters based on individual usage patterns. This multi-functional approach allows the system to maintain standardization benefits while achieving performance optimization through targeted adaptations.
Data Source
AI summary
Methods, systems, and apparatus to reconfigure a computer are disclosed. An example electronic device includes at least one memory, instructions in the electronic device, and processor circuitry to execute instructions to analyze data corresponding to a first configuration of the electronic device to detect a change associated with the electronic device, the first configuration corresponding to a respective first user profile, determine a second configuration of the electronic device based on the detected change, and adjust a configuration of the electronic device from the first configuration to the second configuration.


