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Real-Time Power Analysis of Smart Sensors Using Advanced Debugging Methods
Daniel Gis1, Nils Büscher1, Christian Haubelt1
1Institute of Applied Microelectronics and Computer Engineering, Faculty of Computer Science and Electrical Engineering, University of Rostock, 18059 Rostock, Germany.
Estimating embedded system power consumption is vital for battery-powered devices. A new sensor-in-the-loop method accurately estimates power usage without needing specialized hardware, achieving less than 1% error.
Area of Science:
- Electrical Engineering
- Computer Science
- Embedded Systems
Background:
- Accurate power consumption estimation is critical for embedded systems, especially those with limited power supplies like batteries or energy harvesting.
- Current methods include formal methods, power debugging tools on real hardware, and simulation-based estimations, each with limitations.
- Developing efficient power management strategies requires precise, reproducible power consumption data.
Purpose of the Study:
- To propose a novel method for estimating the power consumption of embedded systems and their firmware.
- To combine the benefits of existing power estimation techniques into a single, efficient approach.
- To enable reproducible, run-time power analysis without requiring dedicated power debugging hardware.
Main Methods:
- Utilizing a sensor-in-the-loop architecture enhanced with power estimation functionality.
- Developing a method that leverages recorded data for run-time analysis.
- Validating the proposed method against traditional power debugging hardware.
Main Results:
- The proposed method achieves an error rate of less than 1% compared to power debugging hardware.
- The technique allows for reproducible power consumption analysis using recorded data.
- The method eliminates the need for specialized power debugging hardware for estimation.
Conclusions:
- The novel sensor-in-the-loop based method offers a reliable and fast approach to estimate embedded system power consumption.
- This technique provides a valuable alternative for systems with constrained power budgets.
- The findings contribute to more efficient design and development of low-power embedded systems.
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