A Study on the Impact of Nodes Density on the Energy Consumption of LoRa

Authors

  • Aizat Faiz Ramli Universiti Kuala Lumpur British Malaysian Institute
  • Muhammad Ikram Shabry Universiti Kuala Lumpur British Malaysian Institute
  • Mohd Azlan Abu Universiti Kuala Lumpur British Malaysian Institute
  • Hafiz Basarudin Universiti Kuala Lumpur British Malaysian Institute

DOI:

https://doi.org/10.3991/ijim.v15i14.19825

Keywords:

IoT, LoRa, LoRaWAN, energy efficiency, node density

Abstract


LoRaWAN is one of the leading Low power wide area network (LPWAN) LPWAN technologies that compete for the formation of big scale Internet of Things (IoT). It uses LoRa protocol to achieve long range, low bit rate and low power communication. Large scale LoRaWAN based IoT deployments can consist of battery powered sensor nodes. Therefore, the energy consumption and efficiency of these nodes are crucial factors that can influence the lifetime of the network. However, there is no coherent experimental based research which identifies the factors that influence the LoRa energy efficiency at various nodes density. In this paper, results on measuring the packet delivery ratio, packet loss, data rate and energy consumption ratio ECR to gauge the energy efficiency of LoRa devices at various nodes density are presented. It is shown that the ECR of LoRa is inversely proportional to the nodes density and that the ECR of the network is smaller at higher traffic indicating better network energy efficiency. It is also demonstrated that at high node density, spreading factor SF of 7 and 9 can improve the energy efficiency of the network by 5 and 3 times, respectively, compare to SF 11.

Author Biographies

Aizat Faiz Ramli, Universiti Kuala Lumpur British Malaysian Institute

Aizat Faiz Ramli is currently a senior lecturer at Electronics Technology section, Universiti Kuala Lumpur British Malaysian Institute. He was the Head of Section for Postgraduate Studies and Research & innovation Coordinator from February 2018 till February 2020 and 2017 till February 2018, respectively. Aizat Faiz was awarded PhD from the University of York, United Kingdom in 2014 and a Master of Engineering degree in Electronic Engineering (MEng) from University of Hull, United Kingdom. His area of expertise and current research interest includes cognitive radio, artificial intelligence, wireless sensor networks and Internet of Things (IOT).

Muhammad Ikram Shabry, Universiti Kuala Lumpur British Malaysian Institute

Muhammad Ikram Shabry graduated from Universiti Kuala Lumpur British Malaysian Institute in Bachelor of Electronic Engineering Technology.

Mohd Azlan Abu, Universiti Kuala Lumpur British Malaysian Institute

Mohd Azlan Abu received the B.Eng (HONS) in Electrical- Electronics from the Universiti Teknologi Malaysia, Malaysia, in 2008, M.Eng in Electrical-Electronics & Telecommunication, from Universiti Teknologi Malaysia, Malaysia in 2010 and PhD in Electronic Engineering, from Universiti Putra Malaysia (UPM), Selangor in 2018. In 2008, he joined Motorola Technology Malaysia, as Research and Development En-gineer. Since December 2010, he has been working in Universiti Kuala Lumpur British Malaysian Institute, Selangor, Malaysia, where he is a Senior Lecturer and Pro-gramme Coordinator for Bachelor of Engineering Technology in Electronics from 2015 until 2017. From 2017 until 2019, he was appointed as Head of Electronic Technology Section, UniKL BMI. Currently, he is appointed as Head of Section, Quality Assurance Section. His current research interests include Artificial Intelli-gence, IoT, Data Analytics, FPGA, Communication systems and Machine Learning.

Hafiz Basarudin, Universiti Kuala Lumpur British Malaysian Institute

Hafiz Basarudin is a senior lecturer at Universiti Kuala Lumpur British Malaysian Institute. He was previously Head of Section for Postgraduate studies. Dr Hafiz graduated with a PhD (2012) and MEng (2008) in electronics engineering from University of Hull (UK) and was a former UniKL BMI student (HND program). His area of expertise including radio propagation, satellite and meteorology.

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Published

2021-07-28

How to Cite

Ramli, A. F., Shabry, M. I., Abu, M. A., & Basarudin, H. (2021). A Study on the Impact of Nodes Density on the Energy Consumption of LoRa. International Journal of Interactive Mobile Technologies (iJIM), 15(14), pp. 157–168. https://doi.org/10.3991/ijim.v15i14.19825

Issue

Vol. 15 No. 14 (2021)

Section

Papers