AURORA: Adaptive spreading factor control for low-power multihop LoRa network

초록

LoRa has gained significant attention for Internet of Things (IoT) applications that require low-power and long-range communication such as animal tracking. However, LoRa’s spreading factor (SF) selection mechanism and 1-hop topology lack effective per-link adaptation to dynamics of the communication channel nor provide comprehensive coverage of moving animals. To address this problem, we present AURORA, an adaptive and distributed SF control scheme for low-power multihop LoRa networks. AURORA exploits the key tradeoff of SF—receiver sensitivity vs. data rate—with a focus on energy efficiency. AURORA accurately predicts the packet delivery ratio (PDR) for each SF using efficient probing and model fitting techniques, enabling rapid per-link SF adaptation to improve both PDR and duty cycle in multihop networks. Through real-world experiments conducted on both indoor and outdoor testbeds, we demonstrate that AURORA effectively reduces energy consumption while ensuring reliable communication and extending network coverage. Compared to state-of-the-art approaches such as ADR+, AURORA improves the PDR by 14% and reduces the duty cycle by 18%.

키워드