Power Emulator for Mobile App Energy Prediction
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Solution Overview
Problem
Users cannot accurately predict the power consumption of mobile applications before installation, leading to inefficient battery usage and difficulty in managing power consumption, especially with continuously sensing applications that run in the background.
Innovation Solution
A communication device comprising a user trace manager, power emulator, and power impact estimator that collects and analyzes sensor and device usage traces to generate hardware usage statistics and compute the increase in power consumption of mobile applications, providing personalized and accurate power consumption predictions before installation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users install mobile applications to understand their power consumption characteristics, then users can obtain actual power consumption data, but users waste time and battery resources through trial-and-error installations
Solution Approach 1:
The system performs power consumption analysis before application installation by collecting sensor usage traces and device usage traces, then using a power emulator to execute the application's executable file and generate hardware usage statistics. This preliminary action allows users to see power consumption estimates without actually installing the application, eliminating the need for trial-and-error installations.
Solution Approach 2:
The system creates a virtual copy of the mobile device environment through a power emulator that can execute application executable files without actual installation. The emulator replicates sensor behavior and device usage patterns, allowing power consumption analysis on a copied environment rather than requiring physical installation on the real device.
2Loss of information
If continuously sensing applications are installed to monitor power consumption, then detailed usage data can be collected, but battery power is depleted in the background without user awareness
Solution Approach 1:
The system collects sensor usage traces and device usage traces during normal device operation, then uses these pre-collected traces in the power emulator to analyze application power consumption. This preliminary data collection allows the system to evaluate continuously sensing applications without actually installing them, preventing background power depletion while still gathering necessary usage information.
Solution Approach 2:
The power emulator acts as an intermediary between the application executable file and the actual mobile device. It processes the application code and generates hardware usage statistics based on collected traces without requiring the application to run on the real device, thus preventing unauthorized background power consumption while still enabling detailed analysis.
3Measurement precision
If a detailed trace-based emulation system is implemented to predict power consumption accurately, then personalized power consumption estimates can be provided, but the system complexity increases
Solution Approach 1:
The system segments the power consumption analysis into distinct functional modules: a user trace manager that collects and manages sensor and device usage traces, a power emulator that executes application code and generates hardware usage statistics, and a power impact estimator that computes power consumption increases. This segmentation manages complexity by dividing the system into specialized components with clear responsibilities.
Solution Approach 2:
The power emulator serves as an intermediary layer that bridges the application executable file and the physical mobile device. It translates application code execution into hardware usage statistics based on collected traces, providing accurate power consumption predictions without requiring direct integration with complex device hardware, thus managing system complexity.
Data Source
AI summary
Disclosed herein is a communication device, which comprises a user trace manager, a power emulator, and a power impact estimator. The user trace manager manages a user's sensor usage trace and device usage trace, which shows the user's mobile device usage pattern. The power emulator executes an executable file of the mobile application to generate hardware usage statistics based on the sensor usage trace and the device usage trace. And the power impact estimator computes an increase in power consumption of the mobile application based on the hardware usage statistics.


