Finnegan, Joseph and Brown, Stephen (2018) An Analysis of the Energy Consumption of LPWA-based IoT Devices. In: 2018 International Symposium on Networks, Computers and Communications (ISNCC). IEEE. ISBN 9781538637791
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Abstract
The unique challenges posed by the breadth of
Internet of Things applications have resulted in the development
of a number of different Low Power Wide Area wireless solutions.
These technologies enable scalable long range networks on cheap
low power devices, facilitating the development of a ubiquitous
Internet of Things. The energy efficiency of these wireless
technologies have a significant impact on battery lifetime. In this
paper we propose an approach to energy efficiency calculations
suited to this new paradigm by focusing on daily throughput.
We present a set of deployment cases, develop energy models
to represent each of the technologies studied, and use these
models to provide a thorough comparison in terms of predicted
device lifetime for a range of daily throughputs. This quantitative
analysis of network device efficiency vs. daily throughput enables
identification of the changeover point between optimal solutions.
Our contributions are the integration of different energy models
that have not been previously compared into a common framework, and the identification of the energy-efficiency crossover
points between these models. This enables the selection of the
most efficient wireless solution for specific Internet of Things
applications, which is a key factor in optimising device lifetime.
Item Type: | Book Section |
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Additional Information: | Cite as: J. Finnegan and S. Brown, "An Analysis of the Energy Consumption of LPWA-based IoT Devices," 2018 International Symposium on Networks, Computers and Communications (ISNCC), Rome, 2018, pp. 1-6, doi: 10.1109/ISNCC.2018.8531068. |
Keywords: | Energy Consumption; Low Power Wide Area wireless; IoT Devices; Throughput; Downlink; Wireless communication; Uplink; Internet of Things; Wireless sensor networks; Batteries; |
Academic Unit: | Faculty of Science and Engineering > Computer Science |
Item ID: | 13342 |
Identification Number: | 10.1109/ISNCC.2018.8531068 |
Depositing User: | Stephen Brown |
Date Deposited: | 01 Oct 2020 15:53 |
Publisher: | IEEE |
Refereed: | Yes |
Related URLs: | |
URI: | https://mural.maynoothuniversity.ie/id/eprint/13342 |
Use Licence: | This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here |
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