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: Chapter in Book/Report/Conference proceedingConference proceeding contributionpeer-review

26 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.

Original languageEnglish
Title of host publicationIPSN '23
Subtitle of host publicationproceedings of the 22nd International Conference on Information Processing in Sensor Networks
Place of PublicationNew York
PublisherAssociation for Computing Machinery
Pages14-26
Number of pages13
ISBN (Electronic)9798400701184
DOIs
Publication statusPublished - 2023
Event22nd ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2023 - San Antonio, United States
Duration: 9 May 202312 May 2023

Conference

Conference22nd ACM/IEEE International Conference on Information Processing in Sensor Networks, IPSN 2023
Country/TerritoryUnited States
CitySan Antonio
Period9/05/2312/05/23

Keywords

  • LoRa
  • Firmware Update Over-The-Air

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