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Accurate Online Energy Consumption Estimation of IoT Devices Using Energest

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Advances on Broad-Band Wireless Computing, Communication and Applications (BWCCA 2019)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 97))

Abstract

Minimizing the energy consumption of Internet of Things (IoT) devices is one of the biggest challenges and crucial issues for the future of a sustainable IoT vision. In order to estimate the remaining device lifetime and optimize its energy consumption, it is necessary to have an accurate online view on the consumed energy with minimal overhead. This is non-trivial, as many factors influence energy consumption, therefore requiring a generic measurement methodology. For example, the Medium Access Control (MAC) protocols have a very important influence on the energy consumption. This paper presents an accurate method for estimating the energy consumption of IoT devices using Energest. Our method combines a device-specific offline profiling phase, with a device and protocol-agnostic online energy estimation methodology. Energy measurements have been performed for different scenarios, using measured values and values from the datasheet, for Carrier Sense Multiple Access (CSMA) and Time Slotted Channel Hopping (TSCH) protocols. Results show that the accuracy of our method is very high, more than 96% for CSMA and more than 82% for TSCH, with very small overhead of 0.11%.

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Notes

  1. 1.

    https://github.com/contiki-ng/contiki-ng.

  2. 2.

    https://github.com/contiki-ng/contiki-ng/wiki/Documentation:-Energest.

  3. 3.

    https://github.com/contiki-ng/contiki-ng.

  4. 4.

    https://github.com/contiki-ng/contiki-ng/wiki/Documentation:-Energest.

  5. 5.

    https://github.com/Zolertia/Resources/wiki/The-Zoul-module.

  6. 6.

    https://zolertia.io/.

  7. 7.

    https://github.com/Zolertia/Resources/wiki/RE-Mote.

  8. 8.

    http://www.ti.com/product/CC2538.

  9. 9.

    https://www.keysight.com.

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Acknowledgments

Part of this research was funded by the Flemish FWO SBO S004017N IDEAL-IoT (Intelligent DEnse and Long range IoT networks) project.

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Authors and Affiliations

  1. IDLab, University of Antwerp – imec, Antwerp, Belgium

    Adnan Sabovic, Carmen Delgado & Jeroen Famaey

  2. IDLab, Ghent University – imec, Ghent, Belgium

    Jan Bauwens & Eli De Poorter

Authors
  1. Adnan Sabovic
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  2. Carmen Delgado
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  3. Jan Bauwens
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  4. Eli De Poorter
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  5. Jeroen Famaey
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Corresponding author

Correspondence to Adnan Sabovic .

Editor information

Editors and Affiliations

  1. Department of Information and Communication Engineering, Fukuoka Institute of Technology, Fukuoka, Japan

    Leonard Barolli

  2. Department of Electronics, University of Antwerp, Antwerp, Belgium

    Peter Hellinckx

  3. Rissho University, Tokyo, Japan

    Tomoya Enokido

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Sabovic, A., Delgado, C., Bauwens, J., De Poorter, E., Famaey, J. (2020). Accurate Online Energy Consumption Estimation of IoT Devices Using Energest. In: Barolli, L., Hellinckx, P., Enokido, T. (eds) Advances on Broad-Band Wireless Computing, Communication and Applications. BWCCA 2019. Lecture Notes in Networks and Systems, vol 97. Springer, Cham. https://doi.org/10.1007/978-3-030-33506-9_32

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  • DOI: https://doi.org/10.1007/978-3-030-33506-9_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-33505-2

  • Online ISBN: 978-3-030-33506-9

  • eBook Packages: EngineeringEngineering (R0)

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