Acesso ao meio em redes LoRa com múltiplas gateways de baixo custo

With the emergence of Low Power Wide Area Network (LPWAN) technologies, as support to Internet of Things (IoT) applications, Long-Range (LoRa) popularity emerged, being actually one of the most up-and-coming LPWAN technologies, despite the low-rate transmissions and duty-cycle restrictions. Such recognition is due to LoRa's suitable characteristics for large-scale IoT networks, which span from long-range communications, guaranteed by its proprietary modulation scheme, to low power consumption, a fundamental feature for IoT sensor networks. The focus of this dissertation is the study of medium access control strategies in large-scale single-channel LoRa networks with multiple gateways with respect to the amount of delivered useful information and network access fairness. Firstly, it is proposed and analysed a medium access control strategy for LoRa networks with multiple single-channel gateways and the same transmission parameters are used by the entire network. It is based on the pure- ALOHA protocol used in LoRa, and each end-device uses control packets to advertise its transmissions. In the following, a new access strategy based on channel hopping is proposed. In this, each ED uses the transmission characteristics that are most convenient to it, with respect to the signal's quality with the single-channel GWs that are in its communication range. These strategies aimed to increase the efficiency of the network, allowing end-devices to transmit faster and increasing the percentage of successfully transmitted packets by reducing the amount of collisions, given the regulation of the competition in the access to the transmission medium.Com o aparecimento das tecnologias Low Power Wide Area Network (LPWAN), como suporte para as aplicações da Internet of Things (IoT), Long- Range (LoRa) tornou-se popular, sendo atualmente uma das tecnologias LPWAN mais promissoras, ainda que as suas transmissões tenham baixas taxas de débito e restrições nos ciclos de trabalho. A popularidade deve-se às características que a tecnologia LoRa possui adequadas para redes IoT de larga escala, que vão desde transmissões de longo alcance, garantidas pelo esquema de modulação que esta utiliza, até ao baixo consumo de energia, aspeto crucial em redes de sensores da IoT. O foco desta dissertação é o estudo de estratégias de controlo de acesso ao meio para redes LoRa de grande escala com canal único e múltiplas gateways, relativamente à quantidade de informação útil entregue e à justiça no acesso ao meio. Inicialmente, é proposto e analisado um esquema de controlo de acesso ao meio para redes LoRa com múltiplas gateways e com um único canal, onde os mesmos parâmetros de transmissão são utilizados por toda a rede. Este é baseado no protocolo ALOHA puro utilizado no LoRa, e cada nó terminal utiliza pacotes de controlo para anunciar as suas transmissões. No seguimento, é proposto uma nova estratégia de acesso ao meio baseado na alteração do canal de transmissão. Neste, cada nó terminal usa as características de transmissão que lhe forem mais favoráveis, relativamente à qualidade de sinal que tem com as gateways que se encontram no seu alcance de comunicação. Estas estratégias visaram aumentar a eficiência da rede, permitindo que os nós terminais transmitam mais rapidamente, e aumentando a percentagem de pacotes transmitidos com sucesso através da redução da quantidade de colisões, possibilitada pela regulação da competição no acesso ao canal de transmissão.Mestrado em Engenharia Eletrónica e Telecomunicaçõe

A neural network propagation model for LoRaWAN and critical analysis with real-world measurements

Among the many technologies competing for the Internet of Things (IoT), one of the most promising and fast-growing technologies in this landscape is the Low-Power Wide-Area Network (LPWAN). Coverage of LoRa, one of the main IoT LPWAN technologies, has previously been studied for outdoor environments. However, this article focuses on end-to-end propagation in an outdoor–indoor scenario. This article will investigate how the reported and documented outdoor metrics are interpreted for an indoor environment. Furthermore, to facilitate network planning and coverage prediction, a novel hybrid propagation estimation method has been developed and examined. This hybrid model is comprised of an artificial neural network (ANN) and an optimized Multi-Wall Model (MWM). Subsequently, real-world measurements were collected and compared against different propagation models. For benchmarking, log-distance and COST231 models were used due to their simplicity. It was observed and concluded that: (a) the propagation of the LoRa Wide-Area Network (LoRaWAN) is limited to a much shorter range in this investigated environment compared with outdoor reports; (b) log-distance and COST231 models do not yield an accurate estimate of propagation characteristics for outdoor–indoor scenarios; (c) this lack of accuracy can be addressed by adjusting the COST231 model, to account for the outdoor propagation; (d) a feedforward neural network combined with a COST231 model improves the accuracy of the predictions. This work demonstrates practical results and provides an insight into the LoRaWAN’s propagation in similar scenarios. This could facilitate network planning for outdoor–indoor environments

Internet of robotic things : converging sensing/actuating, hypoconnectivity, artificial intelligence and IoT Platforms

The Internet of Things (IoT) concept is evolving rapidly and influencing newdevelopments in various application domains, such as the Internet of MobileThings (IoMT), Autonomous Internet of Things (A-IoT), Autonomous Systemof Things (ASoT), Internet of Autonomous Things (IoAT), Internetof Things Clouds (IoT-C) and the Internet of Robotic Things (IoRT) etc.that are progressing/advancing by using IoT technology. The IoT influencerepresents new development and deployment challenges in different areassuch as seamless platform integration, context based cognitive network integration,new mobile sensor/actuator network paradigms, things identification(addressing, naming in IoT) and dynamic things discoverability and manyothers. The IoRT represents new convergence challenges and their need to be addressed, in one side the programmability and the communication ofmultiple heterogeneous mobile/autonomous/robotic things for cooperating,their coordination, configuration, exchange of information, security, safetyand protection. Developments in IoT heterogeneous parallel processing/communication and dynamic systems based on parallelism and concurrencyrequire new ideas for integrating the intelligent “devices”, collaborativerobots (COBOTS), into IoT applications. Dynamic maintainability, selfhealing,self-repair of resources, changing resource state, (re-) configurationand context based IoT systems for service implementation and integrationwith IoT network service composition are of paramount importance whennew “cognitive devices” are becoming active participants in IoT applications.This chapter aims to be an overview of the IoRT concept, technologies,architectures and applications and to provide a comprehensive coverage offuture challenges, developments and applications