TY - GEN
T1 - Enhancing LoRaWAN-based Connectivity for Scalable Smart City Applications
AU - Kulkarni, Parag
AU - Pradeep, Bivin
AU - Raza, Usman
AU - Lakas, Abderrahmane
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - IoT connectivity is a crucial enabler for Smart City applications. Given the plethora of applications each with its own distinct requirements, a variety of connectivity solutions have emerged that cater to this wide spectrum of needs from short-range to long-range, low data rate to high data rate, and the ability to scale up with an increasing network size. Low Power Wide Area Networks (LPWANs) offer a niche in this segment providing long-range, low data rate, and low-cost access suitable for a range of applications. LoRaWAN, one of the technologies under this umbrella, has been one of the front runners in this space. The ready availability of hardware in the market combined with an open specification has led to widespread interest in this technology with network deployments emerging not only from hobbyists but also some of the operators. In this paper, we highlight some opportunities for enhancing the performance and scalability of LoRaWAN-based IoT networks. Towards the same, we first highlight the shortcomings of one of the ACK transmission approaches and propose a remedial solution. Findings show the promise of the proposed solution in improving performance and scalability as the network scales up with a vast majority of the packets being delivered in the first attempt itself (50-100% more in comparison to the default approach) which leads to lower retransmissions and better goodput. We also highlight the practical deployment considerations. These findings would be of interest to stakeholders planning to deploy IoT connectivity for supporting scalable smart city applications using this technology.
AB - IoT connectivity is a crucial enabler for Smart City applications. Given the plethora of applications each with its own distinct requirements, a variety of connectivity solutions have emerged that cater to this wide spectrum of needs from short-range to long-range, low data rate to high data rate, and the ability to scale up with an increasing network size. Low Power Wide Area Networks (LPWANs) offer a niche in this segment providing long-range, low data rate, and low-cost access suitable for a range of applications. LoRaWAN, one of the technologies under this umbrella, has been one of the front runners in this space. The ready availability of hardware in the market combined with an open specification has led to widespread interest in this technology with network deployments emerging not only from hobbyists but also some of the operators. In this paper, we highlight some opportunities for enhancing the performance and scalability of LoRaWAN-based IoT networks. Towards the same, we first highlight the shortcomings of one of the ACK transmission approaches and propose a remedial solution. Findings show the promise of the proposed solution in improving performance and scalability as the network scales up with a vast majority of the packets being delivered in the first attempt itself (50-100% more in comparison to the default approach) which leads to lower retransmissions and better goodput. We also highlight the practical deployment considerations. These findings would be of interest to stakeholders planning to deploy IoT connectivity for supporting scalable smart city applications using this technology.
KW - Internet of Things (IoT)
KW - LPWAN
KW - LoRaWAN
KW - Smart Cities
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UR - http://www.scopus.com/inward/citedby.url?scp=85189623446&partnerID=8YFLogxK
U2 - 10.1109/ANTS59832.2023.10468774
DO - 10.1109/ANTS59832.2023.10468774
M3 - Conference contribution
AN - SCOPUS:85189623446
T3 - International Symposium on Advanced Networks and Telecommunication Systems, ANTS
BT - 2023 IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2023
PB - IEEE Computer Society
T2 - 17th IEEE International Conference on Advanced Networks and Telecommunications Systems, ANTS 2023
Y2 - 17 December 2023 through 20 December 2023
ER -