Finnegan, Joseph and Brown, Stephen and Farrell, Ronan (2018) Evaluating the Scalability of LoRaWAN Gateways for Class B Communication in ns-3. In: 2018 IEEE Conference on Standards for Communications and Networking (CSCN). IEEE, pp. 1-6. ISBN 9781538681466

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Abstract

New wireless technologies have been developed in recent years which enable applications that require the transmission of small amounts of data over long distances in an energy efficient manner. One of these technologies, LoRaWAN, includes a server-initiated communication mode named Class B which provides a deterministic latency for downlink communications. In this paper, we model Class B of LoRaWAN in ns-3 to explore the limits of scale at which this form of bi-directional communication remains feasible in large networks. The simulation results show that the principle restriction on scalability is caused by the duty cycle limits that the gateway must adhere to. In addition, we identify a limitation in the protocol which in certain configurations allows a gateway node to block the future transmission of its own beacon frames. Our contributions are the development of the first implementation and simulation of LoRaWAN Class B in ns-3, and an evaluation of the scalability limits of Class B.

Item Type:	Book Section
Additional Information:	This publication has emanated from research conducted with the financial support of Science Foundation Ireland (SFI) and is co-funded under the European Regional Development Fund under Grant Number 13/RC/2077. Cite as: J. Finnegan, S. Brown and R. Farrell, "Evaluating the Scalability of LoRaWAN Gateways for Class B Communication in ns-3," 2018 IEEE Conference on Standards for Communications and Networking (CSCN), Paris, 2018, pp. 1-6, doi: 10.1109/CSCN.2018.8581759.
Keywords:	Scalability; LoRaWAN Gateways; class B; communincation; ns-3; Logic gates; Downlink; Network servers; Protocols; Uplink; Standards;
Academic Unit:	Faculty of Science and Engineering > Electronic Engineering Faculty of Science and Engineering > Research Institutes > Hamilton Institute Faculty of Science and Engineering > Computer Science
Item ID:	13336
Identification Number:	https://doi.org/10.1109/CSCN.2018.8581759
Depositing User:	Ronan Farrell
Date Deposited:	30 Sep 2020 15:24
Publisher:	IEEE
Refereed:	Yes
URI:	Publisher
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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