SystemC Power Profiling for IoT Device Firmware using Runtime Configurable Models

Rudolf, Jens; Gis, Daniel; Stieber, Sebastian; Haubelt, Christian; Dorsch, Rainer G.

doi:10.1109/meco.2019.8759994

Cited by 3 publications

(5 citation statements)

References 8 publications

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“…In comparison to simulation-based approaches described in [ 13 ] or [ 12 ], we work on the real hardware of the smart sensor. This can be a limitation, if the real hardware is not available yet.…”

Section: Discussionmentioning

confidence: 99%

“…The state-of-the-art approach to evaluate an inertial sensor system is using a simulation model with a so-called virtual prototype. This VP not only simulates the functional behavior of system but also its extra functional properties such as timing, power consumption, memory requirements, etc., i.e., it simulates the used hardware [ 12 ]. For example, in [ 13 ], the authors present a RISC-V processor module which includes a sensor submodule.…”

Section: Related Workmentioning

confidence: 99%

“…This approach does not need the actual hardware to evaluate the developed fusion algorithms but still is quite accurate regarding the behavior of the hardware. In the work [ 12 ], the inertial sensor is simulated using the physical characteristics that can be extracted from its datasheet. However, to accurately simulate complex hardware systems in every detail can become very computational expensive, and it is often not possible to simulate the hardware in real time.…”

Section: Related Workmentioning

confidence: 99%

See 2 more Smart Citations

Investigation of Timing Behavior and Jitter in a Smart Inertial Sensor Debugging Architecture

Gis

Büscher

Haubelt

2021

Sensors

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Due to upcoming higher integration levels of microprocessors, the market of inertial sensors has changed in the last few years. Smart inertial sensors are becoming more and more important. This type of sensor offers the benefit of implementing sensor-processing tasks directly on the sensor hardware. The software development on such sensors is quite challenging. In this article, we propose an approach for using prerecorded sensor data during the development process to test and evaluate the functionality and timing of the sensor firmware in a repeatable and reproducible way on the actual hardware. Our proposed Sensor-in-the-Loop architecture enables the developer to inject sensor data during the debugging process directly into the sensor hardware in real time. As the timing becomes more critical in future smart sensor applications, we investigate the timing behavior of our approach with respect to timing and jitter. The implemented approach can inject data of three 3-DOF sensors at 1.6 kHz. Furthermore, the jitter shown in our proposed sampling method is at least three times lower than using real sensor data. To prove the statistical significance of our experiments, we use a Gage R&R analysis, extended by the assessment of confidence intervals of our data.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Investigation of Timing Behavior and Jitter in a Smart Inertial Sensor Debugging Architecture

Gis

Büscher

Haubelt

2021

Sensors

Self Cite

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“…The second state-of-the-art approach is using a simulation for the power analysis [6][7][8]. This approach allows to do the power analysis for all power states and in a reproducible way.…”

Section: Related Workmentioning

confidence: 99%

“…This approach allows to do the power analysis for all power states and in a reproducible way. However, for the simulation, the power analysis cannot be done in real-time and highly depends on the accuracy of the model, e.g., cycle accurate [7], instruction accurate [6], or component based [8]. The creation of the simulation model for the power analysis might be time-consuming.…”

Section: Related Workmentioning

confidence: 99%

Real-Time Power Analysis of Smart Sensors Using Advanced Debugging Methods

2021

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To achieve a good estimate of the power consumption of an embedded system, including its firmware, is a crucial step in the development of systems with a severely constrained power supply. This is especially true for cases where the device is powered by a small battery or through energy harvesting. The state-of-the-art approaches to measure or estimate the power consumption are formal methods, using power debugging tools with the real hardware or simulation based estimations. In the work at hand, a novel method to estimate the power consumption is proposed, it utilizes the sensor-in-the-loop architecture and enhancing it with a power estimation functionality. The proposed method combines the benefits of former methods, allowing for run-time analysis of the power-consumption in a reproducible way using recorded data without the need for power debugging hardware. In the experiments it is shown that, once set up, the proposed method is able to estimate the power consumption with an error of less than 1 % compared to a power debugging hardware. Thus, the proposed method provides a reliable and fast way to estimate the systems power consumption.

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Advanced Debugging Architecture for Smart Inertial Sensors using Sensor-in-the-Loop

Gis

Büscher

Haubelt

2020

2020 International Workshop on Rapid System Prototyping (RSP)

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SystemC Power Profiling for IoT Device Firmware using Runtime Configurable Models

Cited by 3 publications

References 8 publications

Investigation of Timing Behavior and Jitter in a Smart Inertial Sensor Debugging Architecture

Investigation of Timing Behavior and Jitter in a Smart Inertial Sensor Debugging Architecture

Real-Time Power Analysis of Smart Sensors Using Advanced Debugging Methods

Advanced Debugging Architecture for Smart Inertial Sensors using Sensor-in-the-Loop

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