Banca de DEFESA: JESSIKA CRISTINA DA SILVA

Uma banca de DEFESA de MESTRADO foi cadastrada pelo programa.
STUDENT : JESSIKA CRISTINA DA SILVA
DATE: 30/03/2023
TIME: 09:00
LOCAL: Remota via Google Meet
TITLE:

Performance Evaluation of Data Rate Adaptation Mechanisms for LoRaWAN networks for Scenarios of Livestock in Semi-Confinement

 

KEY WORDS:

LoRaWAN, ADR, Machine Learning, IoT.

PAGES: 60
BIG AREA: Engenharias
AREA: Engenharia Elétrica
SUBÁREA: Telecomunicações
SPECIALTY: Sistemas de Telecomunicações
SUMMARY:

This work aims to investigate Adaptive Data Rate (ADR) mechanisms in LoRaWAN networks as a solution for dynamic IoT scenarios and also propose a new solution based on latter investigations. 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 good compromise between coverage and capacity. This thesis aims to investigate IoT scenarios of livestock in semi-confinement, especially in time-varying scenarios (emergence of concentrated traffic demand, network with mobile sensors, for example). Preliminary 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 an adaptation of classic ADR algorithms to promote flexibility between coverage and capacity in such scenarios.

COMMITTEE MEMBERS:
Interno - 3921178 - VALDEMIR PRAXEDES DA SILVA NETO
Interno - 1412682 - VICENTE ANGELO DE SOUSA JUNIOR
Externo à Instituição - ÁLVARO AUGUSTO MACHADO DE MEDEIROS - UFJF