Energy-Efficient Data Aggregation Point Placement in LoRaWAN Networks for Smart Metering Applications

• Thiago Allisson R. da Silva UFPI / IFMA http://orcid.org/0009-0000-0601-4858
• Geraldo A. Sarmento Neto UFPI https://orcid.org/0009-0008-6009-3989
• Luís H. O. Mendes UFPI https://orcid.org/0009-0007-0249-9086
• Pedro F. F. Abreu UFPI https://orcid.org/0009-0000-2241-320X
• Artur F. S. Veloso UFPI https://orcid.org/0000-0001-6872-5954
• Ricardo A. Lira Rabêlo UFPI https://orcid.org/0000-0003-1482-6404
• Francisco Airton Silva UFPI https://orcid.org/0000-0002-8211-6060
• José Valdemir dos Reis Jr. UFPI https://orcid.org/0000-0002-9556-5471

DOI: https://doi.org/10.5753/sbrc.2025.6348

Resumo

Electric grids have been restructured with Smart Grids (SGs) and the deployment of Advanced Metering Infrastructure (AMI) systems is a fundamental part of this process. The definition of the number of Data Aggregation Points (DAPs) and their installation positions is essential for the operation of an AMI, and this work proposes a method to minimize the number of DAPs to be deployed in a Long Range Wide-Area Network (LoRaWAN) network. The method is evaluated through simulations with up to 1000 Smart Meters (SMs) and compares the performance of the clustering algorithms K-Means, K-Medoids, and Fuzzy C-Means in the placement of DAPs. Furthermore, network transmission capacity is analyzed applying the Spreading Factor (SF) allocation schemes Highest - Spreading Factor Allocation (H-SFA), Closest - Spreading Factor Allocation (C-SFA), and Capture Effect - Spreading Factor Allocation (CE-SFA). The results demonstrate that the method is promising, the Fuzzy C-Means algorithm reduces the number of DAPs by up to 33.33%, and the CE-SFA scheme increases network energy efficiency by up to 228.41 b/J.

Palavras-chave: Clustering, DAP Placement, LoRaWAN, Smart Metering, Spreading Factor Allocation

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