Banca de QUALIFICAÇÃO: JESSIKA CRISTINA DA SILVA

Uma banca de QUALIFICAÇÃO de MESTRADO foi cadastrada pelo programa.
STUDENT : JESSIKA CRISTINA DA SILVA
DATE: 08/10/2020
TIME: 09:00
LOCAL: Via videoconferência - meet.google.com/qbi-vrwh-vhg
TITLE:

Data Rate adaptation mechanism for LoRaWAN networks using machine learning

KEY WORDS:

LoRaWAN, ADR, Machine Learning, IoT.

PAGES: 50
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. The standard ADR technique, defined in the LoRaWAN network protocol, is a simple technique that allows the adjustment of the 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 the compromise between coverage and capacity, especially in time-varying scenarios (emergence of concentrated traffic demand, network with mobile sensors, for example). Preliminary results sing 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, the execution schedule for completing the work is presented.

BANKING MEMBERS:
Presidente - 1412682 - VICENTE ANGELO DE SOUSA JUNIOR
Interno - 3921178 - VALDEMIR PRAXEDES DA SILVA NETO
Externo ao Programa - 345972 - FRED SIZENANDO ROSSITER PINHEIRO
Externo à Instituição - ÁLVARO AUGUSTO MACHADO DE MEDEIROS - UFJF