Análise de desempenho de mecanismos de adaptação de taxa para redes LoRaWAN em cenários de criação de gado em semiconfinamento

Abstract

This work aims to investigate Adaptive Data Rate (ADR) mechanisms in LoRaWAN networks as a solution for dynamic IoT scenarios.The standard ADR technique, defined in the LoRaWAN network protocol, is a simple technique that allows an adjustment of transmission rate by reading the SNR (Signal-to-Noise Ratio) value. Due to the multiplicity and dynamics of IoT scenarios, it is necessary to investigate ADR techniques that establish a compromise between coverage and capacity. This thesis aims to investigate IoT scenarios of semi-intensive and extensive livestock farming, especially in time-varying scenarios (emergence of concentrated traffic demand, network with mobile sensors, for example). Results using the ns-3 simulator demonstrate the need to dynamically adapt the ADR parameters, as each scenario requires different ADR strategies (or different parameterization of pre-existing strategies). Finally, we propose new algorithms by adaptating classic ADR strategies to promote flexibility between coverage and capacity in such scenarios.