Electronic Device Performance Optimization via Predictive Resource Management

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Solution Overview

Problem

Electronic devices experience performance delays and battery inefficiencies due to high CPU load during booting and low memory states, leading to sluggish performance and potential shutdowns.

Innovation Solution

A method that detects hardware features, learns usage patterns using a machine learning model, predicts battery usage time and application launches, and optimizes performance by enabling power-saving modes and clearing memory for efficient application launching.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If the electronic device creates multiple processes during booting, then the device can perform multiple functions, but the CPU load increases and application launch time is delayed

Engineering Contradiction:

Improvefunctional capabilityVSAvoidapplication launch time

Core Design Contradiction:

Adaptability or versatilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by predicting which applications the user is likely to launch next and pre-loading or pre-positioning them in memory before they are actually needed. This preliminary preparation reduces the time required for application launch while maintaining the ability to support multiple functions.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system dynamically adjusts process management based on real-time conditions and user behavior patterns. By using machine learning to analyze usage patterns, the system can dynamically prioritize which processes to maintain in memory and which to terminate, optimizing CPU load and application launch time adaptively.

Inventive Principle:

Principle #15Dynamics

2Speed

If the electronic device maintains more applications in memory, then application launch speed improves, but available memory decreases and device performance deteriorates

Engineering Contradiction:

Improveapplication launch speedVSAvoidavailable memory

Core Design Contradiction:

SpeedVSQuantity of substance

Solution Approach 1:

The system pre-loads only the specific applications that are predicted to be launched next, rather than maintaining all possible applications in memory. This selective pre-loading approach provides fast launch speed for anticipated applications while preserving memory resources for other system operations.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system changes the state of application processes by transitioning them between different memory states (active, dormant, terminated) based on prediction accuracy and current system conditions. This dynamic parameter adjustment optimizes the balance between application launch speed and available memory.

Inventive Principle:

Principle #35Parameter changes

3Power

If the electronic device operates without battery optimization, then full performance is maintained, but battery drains faster and device may shut down at critical times

Engineering Contradiction:

Improveprocessing powerVSAvoidbattery life

Core Design Contradiction:

PowerVSDuration of action of moving object

Solution Approach 1:

The system performs preliminary battery optimization by predicting future battery levels and proactively adjusting power consumption patterns before critical low-battery conditions occur. This includes pre-scheduling task executions and adjusting performance levels to ensure the device remains operational through the next charging cycle.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The system continuously monitors battery level, charging status, and usage patterns, using this feedback to dynamically adjust power management strategies. The machine learning model learns from historical data to optimize the balance between performance and battery conservation in real-time.

Inventive Principle:

Principle #23Feedback

4Productivity

If the electronic device clears memory frequently, then application launch performance improves, but system overhead increases and battery usage is not optimized

Engineering Contradiction:

Improveapplication launch performanceVSAvoidbattery usage efficiency

Core Design Contradiction:

ProductivityVSLoss of energy

Solution Approach 1:

The system performs memory management actions in advance by predicting which applications will be launched and pre-positioning them in memory. This eliminates the need for frequent memory clearing operations, as the predicted applications are already ready to execute, thereby improving launch performance while reducing the energy overhead of memory management.

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS11829778B2Method for enhancing performance of electronic device

Publication Date: 2023.11.28 SAMSUNG ELECTRONICS CO LTD

AI summary

Embodiments herein disclose a method for enhancing a performance of an electronic device. The method includes detecting a plurality of hardware features of the electronic device. Further, the method includes learning a usage pattern of each of the hardware features of the electronic device over a period of time using a machine learning model. Further, the method includes predicting at least one of a remaining usage time of a battery of the electronic device and at least one application to be launched by a user of the electronic device based on the usage pattern of each of the hardware features. Further, the method includes enhancing the performance of the electronic device based on at least one of the predicted remaining usage time of the battery and the at least one predicted application to be launched by the user.