LoRaWAN networks rely on gateways to relay packets from resource-constrained end devices to the network server, creating a potential single point of failure in network infrastructure. While traditional graph centrality metrics exist for general networks, they fail to capture LoRaWAN-specific characteristics such as adaptive data rate (ADR) mechanisms, spreading factor orthogonality, and asymmetric node-gateway connectivity patterns. This paper introduces a gateway criticality metric specifically designed for LoRaWAN networks, as well as an algorithm that employs this metric in an analysis task in order to identify and prioritize critical infrastructure components before failures occur. The metric for gateways presented in this study combines three LoRaWAN-specific factors: connected node count (coverage contribution), exclusive node count (single points of failure), and served traffic volume (application-level importance). Unlike traditional centrality measures, the algorithm presented accounts for ADR's ability to adaptively increase spreading factors when gateways fail, recognizing latent redundancy that becomes accessible during outages. The exclusive nodes are weighted most heavily (50% contribution), as their isolation has immediate, unavoidable impact on network availability. The metric is validated through 300 simulations across diverse network topologies spanning 7 to 50 nodes and 1 to 5 gateways. Results demonstrate strong correlation between criticality scores and measured failure impact. High-criticality gateway failures (C ≥ 0.7) caused packet delivery ratio (PDR) drops of around 60%, while low-criticality failures (C < 0.3) produced up to 25% drops. The metric generalizes across reviewed network scales and topologies, from simple dual-gateway deployments to complex scenarios with 50 nodes and 5 gateways.
Дремов et al. (Tue,) studied this question.