IEEE Access (Jan 2024)

A Minimalistic Distance-Vector Routing Protocol for LoRa Mesh Networks

  • Roger Pueyo Centelles,
  • Roc Meseguer,
  • Felix Freitag,
  • Roger Baig Vinas,
  • Leandro Navarro

DOI
https://doi.org/10.1109/ACCESS.2024.3443605
Journal volume & issue
Vol. 12
pp. 128941 – 128962

Abstract

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LoRa is popular in the Internet of Things (IoT) domain as a Low Power, Wide Area Network (LPWAN) radio technology, providing low-power and long-range communication in the sub-GHz band. Most often, LoRa is used as part of the LoRaWAN architecture with a star-of-stars topology, but it can also be operated standalone. This paper presents and evaluates a minimalistic *RP for building LoRa networks with a more flexible mesh network topology. We propose a *ToA metric that, when used in heterogeneous network topologies, can take better advantage of LoRa’s multiple *SF, and their trade-off between transmission distance and bit rate, and their quasi-orthogonality property. We evaluate the routing protocol with the FLoRa framework and OMNeT++ and compare it with other common routing strategies. Our experiments provide a comprehensive understanding of the routing protocol performance concerning the scalability, throughput, and latency in several topology and network traffic scenarios. When using the ToA metric, we observed in LoRa mesh networks formed by random topologies and heterogeneous links the positive impact of a more balanced Packet Delivery Ratio (PDR) among the nodes with different network centrality, suggesting hence the multi-SF ToA metric to be used for improved PDR in conditions that are expected to occur in real-world systems. Regarding goodput, we observed that using multiple SF simultaneously had a limited impact on low to high traffic loads but dramatically improved throughput and goodput in traffic saturation scenarios. This suggests that multi-SF operation would be preferred to maximize network performance. We observed the best latency performance with multi-SF ToA for low and medium traffic loads, especially for the random topology, where the metric can again take advantage of the node and link heterogeneity.

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