FLoRa: Energy-Efficient, Reliable, and Beamforming-Assisted Over-The-Air Firmware Update in LoRa Networks

Zehua Sun, Tao Ni, Huanqi Yang, Kai Liu, Yu Zhang, Tao Gu, Weitao Xu*

*Corresponding author for this work

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

34 Citations (Scopus)

Abstract

LoRa has emerged as one of the promising long-range and low-power wireless communication technologies for Internet of Things (IoT). With the massive deployment of LoRa networks, the ability to perform Firmware Update Over-The-Air (FUOTA) is becoming a necessity for unattended LoRa devices. LoRa Alliance has recently dedicated the specification for FUOTA, but the existing solution has several drawbacks, such as low energy efficiency, poor transmission reliability, and biased multicast grouping. In this paper, we propose a novel energy-efficient, reliable, and beamforming-assisted FUOTA system for LoRa networks named FLoRa, which is featured with several techniques, including delta scripting, channel coding, and beamforming. In particular, we first propose a novel joint differencing and compression algorithm to generate the delta script for processing gain, which unlocks the potential of incremental FUOTA in LoRa networks. Afterward, we design a concatenated channel coding scheme to enable reliable transmission against dynamic link quality. The proposed scheme uses a rateless code as outer code and an error detection code as inner code to achieve coding gain. Finally, we design a beamforming strategy to avoid biased multicast and compromised throughput for power gain. Experimental results on a 20-node testbed demonstrate that FLoRa improves network transmission reliability by up to 1.51× and energy efficiency by up to 2.65× compared with the existing solution in LoRaWAN. © 2023 Copyright held by the owner/author(s). Publication rights licensed to ACM.
Original languageEnglish
Title of host publicationIPSN '23: Proceedings of the 22nd International Conference on Information Processing in Sensor Networks
PublisherAssociation for Computing Machinery
Pages14–26
ISBN (Print)979-8-4007-0118-4
DOIs
Publication statusPublished - May 2023
Event22nd International Conference on Information Processing in Sensor Networks (IPSN 2023) - San Antonio, TX, United States
Duration: 9 May 202312 May 2023
http://ipsn.acm.org/2023/

Conference

Conference22nd International Conference on Information Processing in Sensor Networks (IPSN 2023)
PlaceUnited States
CitySan Antonio, TX
Period9/05/2312/05/23
Internet address

Bibliographical note

Research Unit(s) information for this publication is provided by the author(s) concerned.

Research Keywords

  • LoRa
  • Firmware Update Over-The-Air

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