Building a test bed for simulation analysis for the internet of things

Mestrado com dupla diplomação com a Universidade Tecnológica e Federal do ParanáThe Internet of Things (IoT) enables the mix between the physical and informational world. Physical objects will be able to see, hear, think together, share information and coordinate decisions, without human interference in a variety of domains. To enable this vision of IoT in large scale is expected of the equipment to be low-cost, mobile, power efficient, computational constrained, and wireless communication enabled. This project performs an extensive overview of the state-of-the-art in communication technologies for IoT, simulation theory and tools. It also describes test bed for IoT simulation and its implementation. The simulation was built with Castalia Simulator (i.e. Wireless Sensor Networks (WSN) network) and INET framework (i.e. IP network), both extends OMNeT++ features. There are two independent networks that communicate through files and exchange information about source, destination, payload and simulation time. Analyzing the outputs is possible to assure that the routing protocol that is provided in the Castalia Simulator does not provide any advantage in terms of packets loss, packets reception or energy consumption.A Internet das Coisas (IoT) permite a mistura entre o mundo físico e informacional. Objetos físicos serão capazes de ver, ouvir, pensar juntos, compartilhar informações e coordenar decisões, sem interferência humana em uma variedade de domínios. Para permitir essa visão de IoT em larga escala, espera-se que o equipamento seja de baixo custo, móvel, eficiente em termos de energia, com restrições computacionais e possibilite a comunicação sem fio. Este projeto faz uma extensa visão geral do estado da arte em tecnologias de comunicação para IoT, teoria de simulação e ferramentas. Também descreve o banco de testes para simulação de IoT e sua implementação. A simulação foi construída com o Simulador Castalia (ou seja, rede WSN) e o framework INET (ou seja, rede IP), ambos estendem os recursos do OMNeT ++. Existem duas redes independentes que se comunicam através de arquivos e trocam informações sobre origem, destino, carga útil e tempo de simulação. Analisando os resultados é possível garantir que o protocolo de roteamento que é fornecido no Simulador Castalia não oferece qualquer vantagem em termos de quebra de pacotes, recepção de pacotes ou consumo de energia

FUZZY BASED SECURITY ALGORITHM FOR WIRELESS SENSOR NETWORKS IN THE INTERNET OF THINGS PARADIGM

Published ThesisThe world is embracing the idea of Internet of Things and Industrial Revolution 4.0. However, this acceptance of computerised evolution is met with a myriad of challenges, where consumers of this technology are also growing ever so anxious about the security of their personal data as well as reliability of data collected by the millions and even billions of sensors surrounding them. Wireless sensor networks are the main baseline technology driving Internet of things; by their very inherent nature, these networks are too vulnerable to attacks and yet the network security tools designed for conventional computer networks are not effective in countering these attacks. Wireless sensors have low computational resources, may be highly mobile and in most cases, these networks do not have a central point which can be marked as an authentication point for the sensors, any node can join or leave whenever they want. This leaves the sensors and the internet of things applications depending on them highly susceptible to attacks, which may compromise consumer information and leave security breaches in situation that need absolute security such as homes or even the cars they drive. There are many possibilities of things that could go wrong when hackers gain control of sensors in a car or a house. There have been many solutions offered to address security of Wireless Sensor Networks; however, most of those solutions are often not customised for African context. Given that most African countries have not kept pace with the development of these underlying technologies, blanket adoption of the solutions developed for consumption in the developed world has not yielded optimal results. The focus of this research was the development of an Intrusion Detection System that works in a hierarchical network structured Wireless Sensor Network, where cluster heads oversee groups of nodes and relay their data packets all the way to the sink node. This is a reactive Intrusion Detection System (IDS) that makes use of a fuzzy logic based algorithm for verification of intrusion detections. This system borrows characteristics of traditional Wireless Sensor Networks in that it is hosted external to the nodes; that is, on a computer or server connected to the sink node. The rational for this is the premise that developing the system in this manner optimises the power and processing resource of nodes because no part of the IDS is found in the nodes and they are left to focus purely on sensing. The Intrusion Detection System makes use of remote Over The Air programming to communicate with compromised nodes, to either shut down or reboot and is designed with the ZigBee protocol in mind. Additionally, this Intrusion Detection System is intended to being part of a larger Internet of Things integration framework being proposed at the Central University of Technology. This framework is aimed at developing an Internet of Things adoption strategy customised for African needs and regionally local consumers. To evaluate the effectiveness of the solution, the rate of false detections being picked out by the security algorithm were reduced through the use of fuzzy logic systems; this resulted in an accuracies of above 90 %. The algorithm is also very light when asymptotic notation is applied, making it ideal for Wireless Sensors. Lastly, we also put forward the Xbee version of the Triple Modular Redundancy architecture, customised for Wireless sensor networks in order to beef-up on the security solution presented in this dissertation

LoRaWAN Network for Fire Monitoring in Rural Environments

The number of forest fires that occurred in recent years in different parts of the world is causing increased concern in the population, as the consequences of these fires expand beyond the destruction of the ecosystem. However, with the proliferation of the Internet of Things (IoT) industry, solutions for early fire detection should be developed. The assessment of the fire risk of an area and the communication of this fact to the population could reduce the number of fires originated by accident or due to the carelessness of the users. This paper presents a low-cost network based on Long Range (LoRa) technology to autonomously evaluate the level of fire risk and the presence of a forest fire in rural areas. The system is comprised of several LoRa nodes with sensors to measure the temperature, relative humidity, wind speed and CO2 of the environment. The data from the nodes is stored and processed in a The Things Network (TTN) server that sends the data to a website for the graphic visualization of the collected data. The system is tested in a real environment and, the results show that it is possible to cover a circular area of a radius of 4 km with a single gateway.This work was partially supported by the “Ministerio de Ciencia, Innovación y Universidades” through the “Ayudas para la adquisición de equipamiento científico-técnico, Subprograma estatal de infraestructuras de investigación y equipamiento científico-técnico (plan Estatal I+D+i 2017-2020)” (project EQC2018-004988-P), by Universidad de Granada through the “Programa de Proyectos de Investigación Precompetitivos para Jóvenes Investigadores. Modalidad A jóvenes Doctores” of “Plan Propio de Investigación y Transferencia 2019” (PPJIA2019.10), by the Campus de Excelencia Internacional Global del Mar (CEI·Mar) through the “Ayudas Proyectos Jóvenes Investigadores CEI·Mar 2019”, (Project CEIJ-020), by the European Union through the ERANETMED (Euromediterranean Cooperation through ERANET joint activities and beyond) (Project ERANETMED3-227 SMARTWATIR)

A real-time packet scheduling system for a 6LoWPAN industrial application

Nowadays, the industrial Wireless Sensor Networks (WSN) are crucial for the monitoring and control of the modern smart factory floor that is relying on them for critical applications and tasks that were performed by wired systems in the past. For this reason, it is required that the transmission mechanisms of wireless sensor networks are efficient and robust and that they guarantee realtime responses with low data losses. Furthermore, it is required that they utilize common networking standards, such as the Internet Protocol (IP), that provides interoperability with already existing infrastructures and offers widely tested security and transmission control protocols. The theoretical part of this document focuses on the description of the current panorama of the industrial WSN, its applications, design challenges and standardizations. It describes the 6LoWPAN standard and the wireless transmission technology that it uses for its lower layers, the IEEE 802.15.4 protocol. Later, it describes the principles behind the wireless scheduling, a state-of-the-art in the IEEE 802.15.4 scheduled channel access and the features of the most used operating systems for WSN. The practical part presents the real-time packet scheduling system for a 6LoWPAN industrial application proposed by this thesis work that adapts the HSDPA scheduling mechanisms to the IEEE 802.15.4 beacon-enabled mode. The system implemented manages the channel access by allocating Guaranteed Time Slots to sensor nodes according to the priority given by three scheduling algorithms that can be selected according to the traffic condition of the network. The system proposed was programmed using Contiki OS. It is based on the eSONIA 6LoWPAN firmware developed for the European Research Project and it was deployed on the FAST WSN for testing. The results, discussion and conclusions are documented at the final sections of this part

A Survey on Smart Agriculture: Development Modes, Technologies, and Security and Privacy Challenges

With the deep combination of both modern information technology and traditional agriculture, the era of agriculture 4.0, which takes the form of smart agriculture, has come. Smart agriculture provides solutions for agricultural intelligence and automation. However, information security issues cannot be ignored with the development of agriculture brought by modern information technology. In this paper, three typical development modes of smart agriculture (precision agriculture, facility agriculture, and order agriculture) are presented. Then, 7 key technologies and 11 key applications are derived from the above modes. Based on the above technologies and applications, 6 security and privacy countermeasures (authentication and access control, privacy-preserving, blockchain-based solutions for data integrity, cryptography and key management, physical countermeasures, and intrusion detection systems) are summarized and discussed. Moreover, the security challenges of smart agriculture are analyzed and organized into two aspects: 1) agricultural production, and 2) information technology. Most current research projects have not taken agricultural equipment as potential security threats. Therefore, we did some additional experiments based on solar insecticidal lamps Internet of Things, and the results indicate that agricultural equipment has an impact on agricultural security. Finally, more technologies (5 G communication, fog computing, Internet of Everything, renewable energy management system, software defined network, virtual reality, augmented reality, and cyber security datasets for smart agriculture) are described as the future research directions of smart agriculture

Prototyping and Evaluation of Sensor Data Integration in Cloud Platforms

The SFI Smart Ocean centre has initiated a long-running project which consists of developing a wireless and autonomous marine observation system for monitoring of underwater environments and structures. The increasing popularity of integrating the Internet of Things (IoT) with Cloud Computing has led to promising infrastructures that could realize Smart Ocean's goals. The project will utilize underwater wireless sensor networks (UWSNs) for collecting data in the marine environments and develop a cloud-based platform for retrieving, processing, and storing all the sensor data. Currently, the project is in its early stages and the collaborating partners are researching approaches and technologies that can potentially be utilized. This thesis contributes to the centre's ongoing research, focusing on the aspect of how sensor data can be integrated into three different cloud platforms: Microsoft Azure, Amazon Web Services, and the Google Cloud Platform. The goals were to develop prototypes that could successfully send data to the chosen cloud platforms and evaluate their applicability in context of the Smart Ocean project. In order to determine the most suitable option, each platform was evaluated based on set of defined criteria, focusing on their sensor data integration capabilities. The thesis has also investigated the cloud platforms' supported protocol bindings, as well as several candidate technologies for metadata standards and compared them in surveys. Our evaluation results shows that all three cloud platforms handle sensor data integration in very similar ways, offering a set of cloud services relevant for creating diverse IoT solutions. However, the Google Cloud Platform ranks at the bottom due to the lack of IoT focus on their platform, with less service options, features, and capabilities compared to the other two. Both Microsoft Azure and Amazon Web Services rank very close to each other, as they provide many of the same sensor data integration capabilities, making them the most applicable options.Masteroppgave i Programutvikling samarbeid med HVLPROG399MAMN-PRO