μMonitor: In-situ energy monitoring with microwatt power consumption

Naderiparizi, Saman; Parks, Aaron; Parizi, Farshid Salemi; Smith, Joshua R.

doi:10.1109/rfid.2016.7488017

Cited by 7 publications

(6 citation statements)

References 7 publications

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“…Therefore, accurately controlling the start and stop of the measurement interval is not possible. On the other hand, the tools proposed by the research community reveal the following shortcomings: (i) complexity and the need to modify the board under test (e.g., [42]- [47]), (ii) offering a limited measurement range (e.g., [42], [48]- [52]), and (iii) low accuracy (e.g., [53], [54]). Due to these concerns, to build the testbed required for the experiments of this paper, we used the EMPIOT tool proposed in [38].…”

Section: Testbed Overviewmentioning

confidence: 99%

Profiling and improving the duty-cycling performance of Linux-based IoT devices

Amirtharaj

Groot

Dezfouli

2019

J Ambient Intell Human Comput

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Minimizing the energy consumption of Linux-based devices is an essential step towards their wide deployment in various IoT scenarios. Energy saving methods such as duty-cycling aim to address this constraint by limiting the amount of time the device is powered on. In this work we study and improve the amount of time a Linux-based IoT device is powered on to accomplish its tasks. We analyze the processes of system boot up and shutdown on two platforms, the Raspberry Pi 3 and Raspberry Pi Zero Wireless, and enhance duty-cycling performance by identifying and disabling time-consuming or unnecessary units initialized in the userspace. We also study whether SD card speed and SD card capacity utilization affect boot up duration and energy consumption. In addition, we propose Pallex, a parallel execution framework built on top of the systemd init system to run a user application concurrently with userspace initialization. We validate the performance impact of Pallex when applied to various IoT application scenarios: (i) capturing an image, (ii) capturing and encrypting an image, (iii) capturing and classifying an image using the the k-nearest neighbor algorithm, and (iv) capturing images and sending them to a cloud server. Our results show that system lifetime is increased by 18.3%, 16.8%, 13.9% and 30.2%, for these application scenarios, respectively. Index Terms-Energy efficiency; boot up; shutdown; edge and fog computing; userspace optimization; machine learning.

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Section: Testbed Overviewmentioning

confidence: 99%

Profiling and improving the duty-cycling performance of Linux-based IoT devices

Amirtharaj

Groot

Dezfouli

2019

J Ambient Intell Human Comput

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“…µMonitor [24] proposes a power monitoring platform based on counting capacitor charging and discharge cycles. For the loads within the range of 1µW to 10mW, the accuracy of µMonitor is almost within 10% of the results obtained from a 16-bit ADC that digitizes the voltage value over a shunt resistor.…”

Section: A Empirical Measurementmentioning

confidence: 99%

“…Due to these challenges, the research community has proposed several power measurement platforms. Based on their main shortcoming, these platforms are classified into the following categories: (i) complex (e.g., [4], [14], [21]- [24]), (ii) limited supported range (e.g., [5], [21], [25]- [29]), and (iii) low accuracy (e.g., [3], [30]). The platforms of the first category present complex circuity, which makes the device costly and hard to build.…”

Section: Introductionmentioning

confidence: 99%

EMPIOT: An energy measurement platform for wireless IoT devices

Dezfouli

Amirtharaj

2018

Journal of Network and Computer Applications

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Profiling and minimizing the energy consumption of resource-constrained devices is an essential step towards employing IoT in various application domains. Due to the large size and high cost of commercial energy measurement platforms, alternative solutions have been proposed by the research community. However, the three main shortcomings of existing tools are complexity, limited measurement range, and low accuracy. Specifically, these tools are not suitable for the energy measurement of new IoT devices such as those supporting the 802.11 technology. In this paper we propose EMPIOT, an accurate, low-cost, easy to build, and flexible power measurement platform. We present the hardware and software components of this platform and study the effect of various design parameters on accuracy and overhead. In particular, we analyze the effects of driver, bus speed, input voltage, and buffering mechanism on sampling rate, measurement accuracy and processing demand. These extensive experimental studies enable us to configure the system in order to achieve its highest performance. We also propose a novel calibration technique and report the calibration parameters under various settings. Using five different IoT devices performing four types of workloads, we evaluate the performance of EMPIOT against the ground truth obtained from a high-accuracy industrial-grade power measurement tool. Our results show that, for very low-power devices that utilize 802.15.4 wireless standard, the measurement error is less than 3.5%. In addition, for 802.11based devices that generate short and high power spikes, the error is less than 2.5%.

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“…Online Energy Monitors: These are relatively simple measurement circuits, ranging from shunt resistors [9], [10] to coulomb counters [11], [12]. While devices can have relatively wide measurement ranges, their main design goal is to bring basic energy awareness to sensor nodes through a single current channel.…”

Section: Existing Measurement Devicesmentioning

confidence: 99%

Measurement and validation of energy harvesting IoT devices

Sigrist

Gómez

Lim

et al. 2017

Design, Automation &Amp; Test in Europe Conference &Amp; Exhibition (DATE), 2017

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With the appearance of wearable devices and the IoT, energy harvesting nodes are becoming more and more important. The design and evaluation of these small standalone sensors and actuators, which harvest limited amounts of energy, requires novel tools and methods. Fast and accurate measurement systems are required to capture the rapidly changing harvesting scenarios and characterize leakage currents and energy efficiencies. The need for real-world experiments creates a demand for compact and portable equipment to perform in-situ power measurements and environmental logging. This work presents the ROCKETLOGGER, a hand-held measurement device that combines both properties: portability and accuracy. The custom analog front-end allows logging at sampling rates up to 64 kSPS. The fast range switching within 1.4 µs guarantees continuous power measurements starting from 4 pW at 1 mV up to 2.75 W at 5.5 V. The software provides remote control and manages data acquisition of up to 13 Mb/ sec in real-time. We extensively characterize the ROCKETLOGGER's performance, demonstrate the need for its properties in three use-cases at different stages of the system design flow, and show its advantages in measuring and validating new harvesting-driven devices for the IoT.

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μMonitor: In-situ energy monitoring with microwatt power consumption

Cited by 7 publications

References 7 publications

Profiling and improving the duty-cycling performance of Linux-based IoT devices

Profiling and improving the duty-cycling performance of Linux-based IoT devices

EMPIOT: An energy measurement platform for wireless IoT devices

Measurement and validation of energy harvesting IoT devices

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