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A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges

Long-Range Wide Area Network (LoRaWAN) is a fast-growing communication system for Low Power Wide Area Networks (LPWAN) in the Internet of Things (IoTs) deployments. LoRaWAN is built to optimize LPWANs for battery lifetime, capacity, range, and cost. LoRaWAN employs an Adaptive Data Rate (ADR) scheme...

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Autores principales: Kufakunesu, Rachel, Hancke, Gerhard P., Abu-Mahfouz, Adnan M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571005/
https://www.ncbi.nlm.nih.gov/pubmed/32899454
http://dx.doi.org/10.3390/s20185044
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author Kufakunesu, Rachel
Hancke, Gerhard P.
Abu-Mahfouz, Adnan M.
author_facet Kufakunesu, Rachel
Hancke, Gerhard P.
Abu-Mahfouz, Adnan M.
author_sort Kufakunesu, Rachel
collection PubMed
description Long-Range Wide Area Network (LoRaWAN) is a fast-growing communication system for Low Power Wide Area Networks (LPWAN) in the Internet of Things (IoTs) deployments. LoRaWAN is built to optimize LPWANs for battery lifetime, capacity, range, and cost. LoRaWAN employs an Adaptive Data Rate (ADR) scheme that dynamically optimizes data rate, airtime, and energy consumption. The major challenge in LoRaWAN is that the LoRa specification does not state how the network server must command end nodes pertaining rate adaptation. As a result, numerous ADR schemes have been proposed to cater for the many applications of IoT technology, the quality of service requirements, different metrics, and radio frequency (RF) conditions. This offers a challenge for the reliability and suitability of these schemes. This paper presents a comprehensive review of the research on ADR algorithms for LoRaWAN technology. First, we provide an overview of LoRaWAN network performance that has been explored and documented in the literature and then focus on recent solutions for ADR as an optimization approach to improve throughput, energy efficiency and scalability. We then distinguish the approaches used, highlight their strengths and drawbacks, and provide a comparison of these approaches. Finally, we identify some research gaps and future directions.
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spelling pubmed-75710052020-10-28 A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges Kufakunesu, Rachel Hancke, Gerhard P. Abu-Mahfouz, Adnan M. Sensors (Basel) Review Long-Range Wide Area Network (LoRaWAN) is a fast-growing communication system for Low Power Wide Area Networks (LPWAN) in the Internet of Things (IoTs) deployments. LoRaWAN is built to optimize LPWANs for battery lifetime, capacity, range, and cost. LoRaWAN employs an Adaptive Data Rate (ADR) scheme that dynamically optimizes data rate, airtime, and energy consumption. The major challenge in LoRaWAN is that the LoRa specification does not state how the network server must command end nodes pertaining rate adaptation. As a result, numerous ADR schemes have been proposed to cater for the many applications of IoT technology, the quality of service requirements, different metrics, and radio frequency (RF) conditions. This offers a challenge for the reliability and suitability of these schemes. This paper presents a comprehensive review of the research on ADR algorithms for LoRaWAN technology. First, we provide an overview of LoRaWAN network performance that has been explored and documented in the literature and then focus on recent solutions for ADR as an optimization approach to improve throughput, energy efficiency and scalability. We then distinguish the approaches used, highlight their strengths and drawbacks, and provide a comparison of these approaches. Finally, we identify some research gaps and future directions. MDPI 2020-09-05 /pmc/articles/PMC7571005/ /pubmed/32899454 http://dx.doi.org/10.3390/s20185044 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Kufakunesu, Rachel
Hancke, Gerhard P.
Abu-Mahfouz, Adnan M.
A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges
title A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges
title_full A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges
title_fullStr A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges
title_full_unstemmed A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges
title_short A Survey on Adaptive Data Rate Optimization in LoRaWAN: Recent Solutions and Major Challenges
title_sort survey on adaptive data rate optimization in lorawan: recent solutions and major challenges
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7571005/
https://www.ncbi.nlm.nih.gov/pubmed/32899454
http://dx.doi.org/10.3390/s20185044
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