Efficient Placement Optimization of LoRaWAN Gateways Using K-Means Clustering

Abstract

As the proliferation of devices on the Internet of Things (IoT) accelerates, the need for efficient communication technologies becomes even more critical, particularly in rural and agricultural regions where connectivity challenges are more pronounced. LoRaWAN, a Low Power Wide Area Network (LPWAN) technology, offers a promising solution due to its long-range capabilities, low power consumption, and cost-effectiveness. However, optimizing gateway placement within LoRaWAN networks remains a key challenge, especially when considering factors such as terrain coverage, node distribution, gateway capabilities, and the need for efficient communication. This paper presents a novel simulation-based approach to optimize LoRaWAN gateway placement using the FLoRa framework integrated with OMNeT++. Our methodology incorporates network performance simulation, optimization data analysis, and K-means clustering to strategically place gateways while addressing constraints such as node separation and gateway capacity. The results demonstrate significant improvements in network coverage, energy efficiency, and a reduction in the number of gateways required, offering a practical solution for the deployment of scalable and efficient IoT networks in resource-constrained environments, particularly rural and agricultural settings.