Efficient online resource allocation in large-scale LoRaWAN networks: A multi-agent approach

The recent proliferation of the Industrial Internet of Things has revealed the potential of Low-Power Wide-Area Networks as a complementary solution to cellular technologies. In this context, the LoRaWAN standard has already been consolidated as one of the most extended technologies in academia and industry for lightweight machine-type communications under negligible energy and cost. As LoRaWAN's Aloha-like nature is known to hinder its reliability, especially under high-traffic and large-scale deployments, numerous time-slotted approaches have been presented as a means to schedule LoRa transmissions accordingly. However, the online allocation of resources based on application constraints has received scant attention in the literature, despite having proved to be significant in real-world deployments. To shed light on this question, this paper proposes a multi-agent approach to efficient resource allocation in multi-SF LoRaWAN networks, addressing architecture design, logic implementation and scalability-oriented evaluation. The integration of agents in the system resulted in network-size improvements of up to 21.6% and 66.7% (for nearby or scatter node distributions within the gateway, respectively). The work provides a set of learned lessons regarding slot-length computation and end-node allocation strategies enabling large-scale collision-free channel access in LoRaWAN networks.