Dissertations / Theses on the topic 'Internet of Things Network (IoTN)'

The Internet of Things is the networking of electronic devices, or “Things”, that enables them to collect and share data, as well as interact with their physical surround- ings. Analyzing this collected data allows us to make smarter economic decisions. These interconnected networks are usually driven by low-powered micro-controllers or cheap CPUs that are designed to function optimally with very little hardware. As scale and computational requirements increase, these micro-controllers are unable to grow without being physically replaced. This thesis proposes a system, IoTA, that assists the Internet of Things by pro- viding a shared computational resource for endpoint devices. This solution extends the functionality of endpoint devices without the need of physical replacement. The IoTA system is designed to be easily integrable to any existing IoT network. This system presents a model that allows for seamless processing of jobs submitted by endpoint devices while keeping scalability and flexibility in mind. Additionally, IoTA is built on top of existing IoT protocols. Evaluation shows there is a significant performance benefit in processing computationally heavy algorithms on the IoTA system as compared to processing them locally on the endpoint devices themselves.

L’internet des objets (IoT) introduit de nouveaux défis pour la sécurité des réseaux. La plupart des objets IoT sont vulnérables en raison d'un manque de sensibilisation à la sécurité des fabricants d'appareils et des utilisateurs. En conséquence, ces objets sont devenus des cibles privilégiées pour les développeurs de malware qui veulent les transformer en bots. Contrairement à un ordinateur de bureau, un objet IoT est conçu pour accomplir des tâches spécifiques. Son comportement réseau est donc très stable et prévisible, ce qui le rend bien adapté aux techniques d'analyse de données. Ainsi, la première partie de cette thèse tire profit des algorithmes de deep learning pour développer des outils de surveillance des réseaux IoT. Deux types d'outils sont explorés: les systèmes de reconnaissance de type d’objets IoT et les systèmes de détection d'intrusion réseau IoT. Pour la reconnaissance des types d’objets IoT, des algorithmes d'apprentissage supervisé sont entrainés pour classifier le trafic réseau et déterminer à quel objet IoT le trafic appartient. Le système de détection d'intrusion consiste en un ensemble d'autoencoders, chacun étant entrainé pour un type d’objet IoT différent. Les autoencoders apprennent le profil du comportement réseau légitime et détectent tout écart par rapport à celui-ci. Les résultats expérimentaux en utilisant des données réseau produites par une maison connectée montrent que les modèles proposés atteignent des performances élevées. Malgré des résultats préliminaires prometteurs, l’entraînement et l'évaluation des modèles basés sur le machine learning nécessitent une quantité importante de données réseau IoT. Or, très peu de jeux de données de trafic réseau IoT sont accessibles au public. Le déploiement physique de milliers d’objets IoT réels peut être très coûteux et peut poser problème quant au respect de la vie privée. Ainsi, dans la deuxième partie de cette thèse, nous proposons d'exploiter des GAN (Generative Adversarial Networks) pour générer des flux bidirectionnels qui ressemblent à ceux produits par un véritable objet IoT. Un flux bidirectionnel est représenté par la séquence des tailles de paquets ainsi que de la durée du flux. Par conséquent, en plus de générer des caractéristiques au niveau des paquets, tel que la taille de chaque paquet, notre générateur apprend implicitement à se conformer aux caractéristiques au niveau du flux, comme le nombre total de paquets et d'octets dans un flux ou sa durée totale. Des résultats expérimentaux utilisant des données produites par un haut-parleur intelligent montrent que notre méthode permet de générer des flux bidirectionnels synthétiques réalistes et de haute qualité
The growing Internet of Things (IoT) introduces new security challenges for network activity monitoring. Most IoT devices are vulnerable because of a lack of security awareness from device manufacturers and end users. As a consequence, they have become prime targets for malware developers who want to turn them into bots. Contrary to general-purpose devices, an IoT device is designed to perform very specific tasks. Hence, its networking behavior is very stable and predictable making it well suited for data analysis techniques. Therefore, the first part of this thesis focuses on leveraging recent advances in the field of deep learning to develop network monitoring tools for the IoT. Two types of network monitoring tools are explored: IoT device type recognition systems and IoT network Intrusion Detection Systems (NIDS). For IoT device type recognition, supervised machine learning algorithms are trained to perform network traffic classification and determine what IoT device the traffic belongs to. The IoT NIDS consists of a set of autoencoders, each trained for a different IoT device type. The autoencoders learn the legitimate networking behavior profile and detect any deviation from it. Experiments using network traffic data produced by a smart home show that the proposed models achieve high performance.Despite yielding promising results, training and testing machine learning based network monitoring systems requires tremendous amount of IoT network traffic data. But, very few IoT network traffic datasets are publicly available. Physically operating thousands of real IoT devices can be very costly and can rise privacy concerns. In the second part of this thesis, we propose to leverage Generative Adversarial Networks (GAN) to generate bidirectional flows that look like they were produced by a real IoT device. A bidirectional flow consists of the sequence of the sizes of individual packets along with a duration. Hence, in addition to generating packet-level features which are the sizes of individual packets, our developed generator implicitly learns to comply with flow-level characteristics, such as the total number of packets and bytes in a bidirectional flow or the total duration of the flow. Experimental results using data produced by a smart speaker show that our method allows us to generate high quality and realistic looking synthetic bidirectional flows

Les réseaux de capteurs visuels sans fil basés sur les réseaux maillés IEEE 802.11 sont des solutions efficaces et adaptées aux systèmes de vidéosurveillance pour surveiller les intrusions dans des zones sélectionnées. Les réseaux de capteurs visuels basés sur IEEE 802.11 offrent des transmissions vidéo à haut débit mais souffrent de problèmes d'inefficacité énergétique. De plus, la transmission vidéo dans les réseaux de capteurs visuels nécessite une qualité de service (QoS) stricte en termes de bande passante et de délai. En outre, il est difficile de réduire la consommation énergétique globale du réseau tout en garantissant une qualité de service garantie en termes de bande passante et de délai dans les réseaux de capteurs visuels sans fil à énergie limitée. La principale contribution de cette thèse est de fournir un réseau de vidéosurveillance économe en énergie sans compromettre l'exigence de qualité de service de la transmission vidéo. Premièrement, nous proposons une nouvelle architecture de réseau hybride IoT pour un système de vidéosurveillance qui détecte et suit un intrus dans la zone de surveillance. Le réseau IoT hybride intègre les réseaux de capteurs visuels multi-sauts basés sur IEEE 802.11 et le réseau LoRa pour fournir un système de vidéosurveillance autonome, économe en énergie et à haut débit. Tirant parti des caractéristiques du réseau LoRa, le réseau LoRa est utilisé comme un réseau toujours actif pour la détection et le suivi préliminaires des mouvements. De plus, le réseau LoRa décide également quels nœuds de capteurs visuels réveiller en fonction des informations de suivi. Le filtre de Kalman est étudié pour suivre la trajectoire de l'intrus à partir des mesures de bruit des capteurs de mouvement à faible puissance afin d'activer uniquement les nœuds de capteurs visuels le long de la trajectoire de l'intrus pour fournir une surveillance vidéo efficace. Nous avons montré par simulation que le filtre de Kalman estime et prédit la trajectoire de l'intrus avec une précision raisonnable. De plus, l'approche de réseau hybride IoT proposée réduit considérablement la consommation d'énergie par rapport à un réseau de capteurs visuels à un seul niveau de surveillance continue traditionnelle et toujours active. Ensuite, la contribution de cette thèse se concentre sur un mécanisme de routage sensible à l'énergie et QoS pour le réseau de capteurs visuels multi-sauts basé sur IEEE 802.11 du réseau hybride IoT. Nous proposons un algorithme de routage qui route un ensemble de flux vidéo vers la passerelle avec une QoS garantie en termes de bande passante et de délai tout en minimisant le nombre de nœuds capteurs visuels impliqués dans le routage. Cela maximise le nombre de nœuds pouvant être complètement désactivés pour optimiser la consommation énergétique globale du réseau sans compromettre les performances QoS. Le problème de routage proposé est formulé comme un programme linéaire entier (ILP) et résolu à l'aide d'un algorithme branch-and-bound. Grâce à la simulation informatique, les performances de l'approche proposée sont comparées aux algorithmes de routage de pointe existants dans la littérature. Les résultats montrent clairement que le mécanisme proposé permet d'économiser une quantité significative de la consommation d'énergie globale tout en garantissant la QoS en termes de bande passante et de délai
Wireless visual sensor networks based on IEEE 802.11 mesh networks are effective and suitable solutions for video surveillance systems in monitoring intrusions in selected areas. The IEEE 802.11-based visual sensor networks offer high bit rate video transmissions but suffer from energy inefficiency issues. Moreover, the video transmission in the visual sensor networks requires strict quality of service (QoS) in terms of bandwidth and delay. Also, it is challenging to decrease the overall energy consumption of the network while assuring guaranteed QoS in terms of bandwidth and delay in energy-constrained wireless visual sensor networks. The main contribution of this dissertation is to provide an energy-efficient video surveillance network without compromising the QoS requirement of video transmission. First, we propose a new hybrid IoT network architecture for a video surveillance system that detects and tracks an intruder in the monitoring area. The hybrid IoT network integrates the IEEE 802.11-based multi-hop visual Sensor Networks and LoRa network to provide an autonomous, energy-efficient, high-bitrate video surveillance system. Leveraging the LoRa network characteristics, the LoRa network is utilized as an always-active network for preliminary motion detection and tracking. Moreover, the LoRa network also decides which visual sensor nodes to wake up depending on the tracking information. The Kalman filter is investigated to track the intruder's trajectory from noise measurements of low-power motion sensors to activate only the visual sensor nodes along the intruder's trajectory to provide effective video vigilance. We showed through simulation that Kalman filter estimates and predicts intruder trajectory with reasonable accuracy. Moreover, the proposed hybrid IoT network approach reduces energy consumption significantly compared with a traditional, always active continuous monitoring single-tier visual sensor network. Next, the contribution of this dissertation focuses on an energy-aware and QoS routing mechanism for the IEEE 802.11-based multi-hop visual sensor network of the hybrid IoT network. We propose a routing algorithm that routes a set of video streams to the gateway with guaranteed QoS in terms of bandwidth and delay while minimizing the number of visual sensor nodes that are involved in routing. This maximizes the number of nodes that can be turned off completely to optimize the overall energy consumption of the network without compromising QoS performance. The proposed routing problem is formulated as an Integer Linear Program (ILP) and solved using the branch-and-bound algorithm. Through computer simulation, the performance of the proposed approach is compared with the existing state-of-the-art routing algorithms from the literature. The results clearly show that the proposed mechanism saves a significant amount of the overall energy consumption while guaranteeing QoS in terms of bandwidth and delay

This thesis summarizes my project in setting up a Thread network. The idea of this project was presented by the company ÅF in Karlstad, Sweden. ÅF wishes to upgrade their current demonstrator for IoT. The current demonstrator includes Azure Cloud component, Raspberry Pi, Bluetooth and Arduino components. The upgrade includes implementing Thread technology together with Thread verified hardware from Nordic semiconductor and the Raspberry Pi Foundation. Thread is an IoT mesh networking protocol that was released year 2014. Compared to Bluetooth it offers IP communication (including IPv6) combined with higher reliability, performance and security. The process of installing, compiling and configuring the Thread network is explained. The result is an operational thread network that has sensor devices sending data to an HTTP web server, where the data is stored and monitored. Though, there are many improvements and functions that can be implemented to make this demonstrator more appealing.

An information technology that can combine the physical world and virtual world is desired. The Internet of Things (IoT) is a concept system that uses Radio Frequency Identification (RFID), WSN and barcode scanners to sense and to detect physical objects and events. This information is shared with people on the Internet. With the announcement of the Smarter Planet concept by IBM, the problem of how to share this data was raised. However, the original design of WSN aims to provide environment monitoring and control within a small scale local network. It cannot meet the demands of the IoT because there is a lack of multi-connection functionality with other WSNs and upper level applications. As various standards of WSNs provide information for different purposes, a hybrid system that gives a complete answer by combining all of them could be promising for future IoT applications. This thesis is on the subject of `Federated Sensor Network' design and architectural development for the Internet of Things. A Federated Sensor Network (FSN) is a system that integrates WSNs and the Internet. Currently, methods of integrating WSNs and the Internet can follow one of three main directions: a Front-End Proxy solution, a Gateway solution or a TCP/IP Overlay solution. Architectures based on the ideas from all three directions are presented in this thesis; this forms a comprehensive body of research on possible Federated Sensor Network architecture designs. In addition, a fully compatible technology for the sensor network application, namely the Sensor Model Language (SensorML), has been reviewed and embedded into our FSN systems. The IoT as a new concept is also comprehensively described and the major technical issues discussed. Finally, a case study of the IoT in logistic management for emergency response is given. Proposed FSN architectures based on the Gateway solution are demonstrated through hardware implementation and lab tests. A demonstration of the 6LoWPAN enabled federated sensor network based on the TCP/IP Overlay solution presents a good result for the iNET localization and tracking project. All the tests of the designs have verified feasibility and achieve the target of the IoT concept.

The market of IOT devices continues to grow at a rapid speed as well as constrained wireless sensor networks. Today, the main network paradigm is host centric where a users have to specify which host they want to receive their data from. Information-centric networking is a new paradigm for the future internet, which is based on named data instead of named hosts. With ICN, a user needs to send a request for a perticular data in order to retrieve it. When sent, any participant in the network, router or server, containing the data will respond to the request. In order to achieve low latency between data creation and its consumption, as well as being able to follow data which is sequentially produced at a fixed rate, an algortihm was developed. This algortihm calculates and determines when to send the next interest message towards the sensor. It uses a ‘one time subscription’ approach to send its interest message in advance of the creation of the data, thereby enabling a low latency from data creation to consumption. The result of this algorithm shows that a consumer can retrieve the data with minimum latency from its creation by the sensor over an extended period of time, without using a publish/subscribe system such as MQTT or similar which pushes their data towards their consumers. The performance evaluation carried out which analysed the Content Centric Network application on the sensor shows that the application has little impact on the overall round trip time in the network. Based on the results, this thesis concluded that the ICN paradigm, together with a ’one-time subscription’ model, can be a suitable option for communication within the IoT domain where consumers ask for sequentially produced data.

Due to the ever increasing supply of new Internet of Things (IoT) devices being added onto a network, it is vital secure the devices from incoming cyber threats. The manufacturing process of creating and developing a new IoT device allows many new companies to come out with their own device. These devices also increase the network risk because many IoT devices are created without proper security implementation. Utilizing traffic patterns as a method of device type detection will allow behavior identification using only Internet Protocol (IP) header information. The network traffic captured from 20 IoT devices belonging to 4 distinct types (IP camera, on/off switch, motion sensor, and temperature sensor) are generalized and used to identify new devices previously unseen on the network. Our results indicate some categories have patterns that are easier to generalize, while other categories are harder but we are still able recognize some unique characteristics. We also are able to deploy this in a test production network and adapted previous methods to handle streaming traffic and an additional noise categorization capable of identify non-IoT devices. The performance of our model is varied between classes, signifying that much future work has to be done to increase the classification score and overall usefulness.
Master of Science
IoT (Internet of Things) devices are an exploding field, with many devices being created, manufactured, and utilized per year. With the rise of so many internet capable devices, there is a risk that the devices may have vulnerabilities and exploits able to allow unauthorized users to access. While a problem for a consumer network, this is an increased problem in an enterprise network, since much of the information on the network is sensitive and should be kept confidential and private. While a ban of IoT devices on a network is able to solve this problem, with the rise of machine learning able to characterize and recognize patterns, a smarter approach can be created to distinguish when and which types of IoT devices enter the network. Previous attempts to identify IoT devices used signature schemes specific to a single device, but this paper aims to generalize traffic behaviors and identifying a device category rather than a specific IoT device to ensure future new devices can also be recognized. With device category identification in place on an internet network, smarter approaches can be implemented to ensure the devices remain secure while still able to be used.

An increasing number of devices, from coffee makers to electric kettles, are becoming connected to the Internet. These are all a part of the Internet of Things, or IoT. Each device generates unique network traffic and power consumption patterns. Until now, there has not been a comprehensive set of data that captures these traffic and power patterns. This thesis documents how we collected 10 to 15 weeks of network traffic and power consumption data from 15 different IoT devices and provides an analysis of a subset of 6 devices. Devices including an Amazon Echo Dot, Google Home Mini, and Google Chromecast were used on a regular basis and all of their network traffic and power consumption was logged to a MySQL database. The database currently contains 64 million packets and 71 gigabytes of data and is still growing in size as more data is collected 24/7 from each device. We show that it is possible to see when users are asking their smart speaker a question or whether the lights in their home are on or off based on power consumption and network traffic from the devices. These trends can be seen even if the data being sent is encrypted.

Internet of Things is rapidly evolving. This thesis includes a study of single-board computers suitable for machine-to-machine communication together with the developing process of a sensor network integrated with a bidirectional communication platform. Raspberry Pi was selected as the single-board computer used in the proposed system. The Message Queuing Telemetry Transport protocol was selected as main communication protocol to handle all exchange of information between the network and the bidirectional communication platform. It was selected because of its reliability, low bandwidth and publish/subscribe architecture. Decision-making procedures were implemented to work with both local sensor data and data from different Message Queuing Telemetry Transport streams, such as GPS data, used to calculate the distance between the user’s smart phone and the office to prepare the workstation, temperature sensors and ambient light sensors controlling Philips HUE light bulbs. The finished sensor network was design to work within office environments to prepare workstations and monitor the work climate. The number of sensors connected to the single-board computer has a major impact in the CPU usage. Measurements and calculations show that 17 connected physical sensors will cause a CPU usage of 96%.

Society is moving towards an “always connected” paradigm, where the Internet user is shifting from persons to things, leading to the so called Internet of Things (IoT) scenario. The IoT vision integrates a large number of technologies and foresees to embody a variety of smart objects around us (such as sensors, actuators, smartphones, RFID, etc.) that, through unique addressing schemes and standard communication protocols, are able to interact with each Others and cooperate with their neighbors to reach common goals [2, 3]. IoT is a hot research topic, as demonstrated by the increasing attention and the large worldwide investments devoted to it. It is believed that the IoT will be composed of trillions of elements interacting in an extremely heterogeneous way in terms of requirements, behavior and capabilities; according to [4], by 2015 the RIFD devices alone will reach hundreds of billions. Unquestionably, the IoT will pervade every aspect of our world and will have a huge impact in our everyday life: indeed, as stated by the US National Intelligence Council (NIC) [5], “by 2025 Internet nodes may reside in everyday things − food packages, furniture, paper documents, and more”. Then, communications will not only involve persons but also things thus bringing about the IoT environment in which objects will have virtual counterparts on the Internet. Such virtual entities will produce and consume services, collaborate toward common goals and should be integrated with all the other services. One of the biggest challenges that the research community is facing right now is to be able to organize such an ocean of devices so that the discovery of objects and services is performed efficiently and in a scalable way. Recently, several attempts have been made to apply concepts of social networking to the IoT. There are scientific evidences that a large number of individuals tied in a social network can provide far more accurate answers to complex problems than a single individual (or a small group of – even knowledgeable – individuals) [1]. The exploitation of such a principle, applied to smart objects, has been widely investigated in Internet-related researches. Indeed, several schemes have been proposed that use social networks to search Internet resources, to route traffic, or to select effective policies for content distribution. The idea that the convergence of the “Internet of Things” and the “Social Networks” worlds, which up to now were mostly kept separate by both scientific and industrial communities, is possible or even advisable is gaining momentum very quickly. This is due to the growing awareness that a “Social Internet of Things” (SIoT) paradigm carries with it many desirable implications in a future world populated by objects permeating the everyday life of human beings. Therefore, the goal of this thesis is to define a possible architecture for the SIoT, which includes the functionalities required to integrate things into a social network, and the needed strategies to help things to create their relationships in such a way that the resulting social network is navigable. Moreover, it focuses on the trustworthiness management, so that interaction among objects that are friends can be done in a more reliable way and proposes a possible implementation of a SIoT network. Since this thesis covers several aspects of the Social internet of Things, I will present the state of the art related to the specific research activities at the beginning of every Chapter. The rest of the thesis is structured as follows. In Chapter 1, I identify appropriate policies for the establishment and the management of social relationships between objects, describe a possible architecture for the IoT that includes the functionalities required to integrate things into a social network and analyze the characteristics of the SIoT network structure by means of simulations. Chapter 2 addresses the problem of the objects to manage a large number of friends, by analyzing possible strategies to drive the objects to select the appropriate links for the benefit of overall network navigability and to speed up the search of the services. In Chapter 3, I focus on the problem of understanding how the information provided by members of the social IoT has to be processed so as to build a reliable system on the basis of the behavior of the objects and define two models for trustworthiness management starting from the solutions proposed for P2P and social networks. Chapter 4 presents an implementation of a SIoT platform and its major functionalities: how to register a new social object to the platform, how the system manages the creation of new relationships, and how the devices create groups of members with similar characteristics. Finally, in Chapter 5, conclusions will be drawn regarding the effectiveness of the proposed Introduction 3 algorithms, and some possible future works will be sketched

Twenty years ago, if someone said that every object could have its own identity, no one would agree and some might even think that was crazy. However, it turns out that the wild imagination is possible today. With the help of the Internet of Things (IoT), it is convenient to identify any objects with RFID (Radio Frequency Identification) and control the objects via the Internet. In the near future, people will even make the IoT network visible, thus all the information on the Internet can become dynamic and much easier to understand than numbers to be.   At the moment, Guiyang Municipal Science & Technology Bureau is planning to design and apply visualization technique to logistics, the focus of Guizhou Provincial logistic network in the IoT era. This is a good opportunity for different kinds of enterprises in theGuizhoudistrict or even in the whole country.   This thesis focuses on three problems, namely, discussion on the use of visualization techniques in IoT, the necessary preparation of manufacturing industry to join in the visible IoT and measures available that the government can adopt. The exploratory case study in this thesis is about the visualization technique in IoT in manufacturing industry in theGuizhouProvince. A company was selected for the case study to explore the situation inGuizhouProvince. The related information was collected through interviews with relevant personnel and observation in the company. To bring a clear view of the situation and provide enterprises with information for reference, SWOT analysis is adopted to evaluate the strength and weakness in both the internal and external environment. Those measures that government can take to promote its development include unification in standards, support in research and development of technology and emphasis on personal privacy.   The conclusion shows that the use of visualization techniques in IoT can promote information transmission both in effectiveness and efficiency, and control the supply chain as well as special processes in an efficient way. Discussions have been conducted on four techniques which are able to realize visualization, including GPS, RFID, bar code and machine vision. The preparation that needs to be done in a progressive way, of manufacturing enterprises mainly involves three aspects: equipment, system, and management; which have been discussed in detail in this study. Only totally combining the three aspects, not a single one can be omitted, can enterprises achieve the goal of growth in benefit and costs reduction through the use of IoT. Due to immaturity of the emerging network and technology, in the future, the IoT still has a long way to go. Certainly, we should not ignore the followed huge benefit and improvement that IoT can bring.

La virtualizzazione permette a diverse applicazioni di condividere lo stesso dispositivo IoT. Tuttavia, in ambienti eterogenei, reti di dispositivi IoT virtualizzati fanno emergere nuove sfide, come la necessità di fornire on-the-fly e in maniera dinamica, elastica e scalabile, gateway. NFV è un paradigma progettato per affrontare queste nuove sfide. Esso sfrutta tecnologie di virtualizzazione standard per consolidare specifici elementi di rete su generico hardware commerciale. Questa tesi presenta un'architettura NFV per gateway IoT distribuiti, nella quale istanze software dei moduli dei gateway sono ospitate su un'infrastruttura NFV distribuita, la quale è operata e gestita da un IoT gateway Provider. Considereremo diversi IoT Provider, ciascuno con le proprie marche, o loro combinazioni, di sensori e attuatori/robot. Ipotizzeremo che gli ambienti dei provider siano geograficamente distribuiti, per un'efficiente copertura di regioni estese. I sensori e gli attuatori possono essere utilizzati da una varietà di applicazioni, ciascuna delle quali può avere diversi requisiti per interfacce e QoS (latenza, throughput, consumi, ecc...). L'infrastruttura NFV consente di effettuare un deployment elastico, dinamico e scalabile dei moduli gateway in questo ambiente eterogeneo e distribuito. Inoltre, l'architettura proposta è in grado di riutilizzare moduli il cui deployment è stato precedentemente compiuto. Ciò è ottenuto attraverso Service Function Chaining e un'orchestrazione dinamica a runtime. Infine, presenteremo un prototipo basato sulla piattaforma OpenStack.

Algumas palavras e definições comumente utilizadas quando se está falando de Software-Defined Networking, como programabilidade, flexibilidade, ou gerenciamento centralizado, parecem muito apropriadas ao contexto de um outro paradigma de rede: Internet of Things. Em redes domésticas já não é incomum a existência de dispositivos projetados para segurança, climatização, iluminação, monitoramento de saúde e algumas formas de automação que diferem entre si em diversos aspectos, como no modo de operar e de se comunicar. Lidar com este tipo de cenário, que pode diferir bastante daquilo que estamos acostumados na gerência de redes e serviços, fazendo uso dos recursos tradicionais como ferramentas e protocolos bem estabelecidos, pode ser difícil e, em alguns casos, inviável. Com o objetivo de possibilitar o monitoramento remoto de pacientes com doenças crônicas através de dispositivos de healthcare disponíveis no mercado, uma proposta de middleware foi desenvolvida em um projeto de pesquisa para contornar as limitações relacionadas à interoperabilidade, coleta de dados, gerência, segurança e privacidade encontradas nos dispositivos utilizados. O middleware foi projetado com o intuito de executar em access points instalados na casa dos pacientes. Contudo, as limitações de hardware e software do access point utilizado refletem no desenvolvimento, pois restringem o uso de linguagens de programação e recursos que poderiam agilizar e facilitar a implementação dos módulos e dos mecanismos necessários. Os contratempos encontrados no desenvolvimento motivaram a busca por alternativas, o que resultou na refatoração do middleware através de Software-Defined Networking, baseando-se em trabalhos que exploram o uso desse paradigma em redes domésticas. O objetivo deste trabalho é verificar a viabilidade da utilização de Software-Defined Networking no contexto de Internet of Things, mais especificamente, aplicado ao serviço de monitoramento de pacientes da proposta anterior e explorar os possíveis benefícios resultantes. Com a refatoração, a maior parte da carga de serviços da rede e do monitoramento foi distribuída entre servidores remotos dedicados, com isso os desenvolvedores podem ir além das restrições do access point e fazer uso de recursos antes não disponíveis, o que potencializa um processo de desenvolvimento mais ágil e com funcionalidades mais complexas, ampliando as possibilidades do serviço. Adicionalmente, a utilização de Software-Defined Networking proporcionou a entrega de mais de um serviço através de um único access point, escalabilidade e autonomia no gerenciamento das redes e dos dispositivos e na implantação de serviços, fazendo uso de recursos do protocolo OpenFlow, e a cooperação entre dispositivos e serviços a fim de se criar uma representação digital mais ampla do ambiente monitorado.
Some words and definitions usually employed when talking about Software-Defined Networking such as programmability, frexibility, or centralized management sound very appropriate to the context of another network paradigm: Internet of Things. The presence of devices designed for security, air conditioning, lighting, health monitoring and some other automation resources have become common in home networks; those devices may be different in many ways, such as the way they operate and communicate, between others. Dealing with this kind of scenario may differ in many ways from what we are familiar regarding networking and services management; the use of traditional management tools and protocols may be hard or even unfeasible. Aiming to enable the health monitoring of patients with chronical illnesses through using off-the-shelf healthcare devices a middleware proposal was developed in a research project to circumvent interoperability, data collecting, management, security and privacy issues found in employed devices. The middleware was designed to run on access points in the homes of the patients. Although hardware and software limitations of the used access points reflect on the development process, because they restrict the use of programming languages and resources that could be employed to expedite the implementation of necessary modules and features. Development related mishaps have motivated the search for alternatives resulting in the middleware refactoring through Software-Defined Networking, based on previous works where that paradigm is used in home networks. This work aims to verify the feasability of the employment of Software- Defined Networking in the Internet of Things context, and its resulting benefits; specifically in the health monitoring of chronic patients service from the previous proposal. After refactoring most of the network and services load was distributed among remote dedicated servers allowing developers to go beyond the limitations imposed by access points constraints, and to make use of resources not available before enabling agility to the development process; it also enables the development of more complex features expanding services possibilities. Additionally Software-Defined Networking employment provides benefits such as the delivering of more than only one service through the same access point; scalability and autonomy to the network and devices monitoring, as to the service deployment through the use of OpenFlow resources; and devices and services cooperation enabling the built of a wider digital representation of the monitored environment.

The super collision between the Internet phenomenon and the wireless communication revolution gives birth to a wealth of novel research problems, design challenges and standardization activities. Within this domain, spontaneous wireless IP networking are probably the most extreme example of new ''particles'' born from the collision. Indeed, these particles defy the laws of the Internet in many ways. The absorption of such peculiar particles in the global IP network has already started thanks to pioneering algorithmic and protocol work -- for instance OLSR -- and through the deployment of wireless mesh networks around the world, such as urban community wireless networks. With the recent revolutions in North Africa, and movements such as Occupy Wall Street, the prospect of spontaneous wireless IP networking has become even more attractive on social and political grounds. Dedicated conferences have recently been organized, and as a result, ambitious, multi-million dollar initiatives have been launched (e.g. the US Government-funded project Commotion Wireless, or the EU-funded initiative CONFINE). However, spontaneous IP wireless networks are not yet widely deployed because pioneer work such as OLSR is vastly insufficient to fully bridge the gap between the Internet and these new networks. This thesis presents work that analyzes this gap and proposes some solutions as to how to bridge it. The focus is put on three domains: a first part presents work in the domain of wireless mesh and ad hoc networks. A second part presents work on sensor networks and in the Internet of Things. And the last part presents work in the domain of delay tolerant networking and vehicular networks.

Diploma thesis deals with the implementation of LTE Cat-M1 technology in simulator NS--3 (Network Simulator 3). The theoretical part of the thesis summarizes key terms concerning IoT (Internet of Things), M2M (Machine-to-Machine) communication, LTE (Long Term Evolution) and LPWA (Low-Power Wide Area) networks. The practical part summarizes the possibilities of currently available modules for cellular technologies for NS-3, ie. the LENA module and the subsequent extension of LENA+ and ELENA. Simulation scenarios offer a comparison of LTE/LTE-A and LTE Cat-M1 (also known as eMTC - enhanced Machine Type Communication) technologies for M2M communication. The results of the simulations are well-arranged in the form of graphs and discussed at the end of the thesis.

L'Internet des objets (IoT), ne comprenant à l'origine que quelques dispositifs de détection simple, atteint aujourd’hui 34 milliards d’objets connectés d'ici fin 2020. Ces objets ne peuvent plus être définis comme de simples capteurs de surveillance. Les capacités de l'IoT ont été améliorées ces dernières années tandis-que que les capacités de calcul et de stockage de masse sont devenus des marchandises. Aux débuts de l'IoT, le traitement et le stockage étaient généralement effectués dans le cloud. Les nouvelles architectures IoT sont capables d'exécuter des tâches complexes directement sur l'appareil, permettant ainsi le concept d'un continuum de calcul étendu. Les scénarios critiques et temps réel, comme par exemple la détection de véhicules autonomes, la surveillance de zone ou le sauvetage en cas de catastrophe, nécessitent que l’ensemble des acteurs impliqués soient coordonnés et collaborent sans interaction humaine vers un objectif commun, partageant des données et des ressources, même dans les zones couvertes par des réseaux intermittents. Cela pose de nouveaux problèmes dans les systèmes distribués, la gestion des ressources, l'orchestration des appareils et le traitement des données. Ce travail propose un nouveau cadre de communication et d'orchestration, à savoir le C-Continuum, conçu dans des architectures IoT hétérogènes à travers plusieurs scénarios d'application. Ce travail se concentre pour gérer les ressources sur deux macro-scénarios clés de durabilité : (a) la détection et la sensibilisation à l'environnement, et (b) le soutien à la mobilité électrique. Dans le premier cas, un mécanisme de mesure de la qualité de l'air sur une longue période avec différentes applications à l'échelle mondiale (3 continents et 4 pays) est introduit. Le système a été développé en interne depuis la conception du capteur jusqu'aux opérations de mist-computing effectuées par les nœuds. Dans le deuxième scénario une technique pour transmettre de grandes quantités de données, entre un véhicule en mouvement et un centre de contrôle est proposé. Ces données sont de haute granularité temporelle relatives et permettent conjointement d'allouer des tâches sur demande dans le continuum de calcul
As Internet of Things (IoT), originally comprising of only a few simple sensing devices, reaches 34 billion units by the end of 2020, they cannot be defined as merely monitoring sensors anymore. IoT capabilities have been improved in recent years as relatively large internal computation and storage capacity are becoming a commodity. In the early days of IoT, processing and storage were typically performed in cloud. New IoT architectures are able to perform complex tasks directly on-device, thus enabling the concept of an extended computational continuum. Real-time critical scenarios e.g. autonomous vehicles sensing, area surveying or disaster rescue and recovery require all the actors involved to be coordinated and collaborate without human interaction to a common goal, sharing data and resources, even in intermittent networks covered areas. This poses new problems in distributed systems, resource management, device orchestration,as well as data processing. This work proposes a new orchestration and communication framework, namely CContinuum, designed to manage resources in heterogeneous IoT architectures across multiple application scenarios. This work focuses on two key sustainability macroscenarios: (a) environmental sensing and awareness, and (b) electric mobility support. In the first case a mechanism to measure air quality over a long period of time for different applications at global scale (3 continents 4 countries) is introduced. The system has been developed in-house from the sensor design to the mist-computing operations performed by the nodes. In the second scenario, a technique to transmit large amounts of fine-time granularity battery data from a moving vehicle to a control center is proposed jointly with the ability of allocating tasks on demand within the computing continuum

yes
The current electricity grid suffers from numerous challenges due to the lack of an effective energy management strategy that is able to match the generated power to the load demand. This problem becomes more pronounced with microgrids, where the variability of the load is obvious and the generation is mostly coming from renewables, as it depends on the usage of distributed energy sources. Building a smart microgrid would be much more economically feasible than converting the large electricity grid into a smart grid, as it would require huge investments in replacing legacy equipment with smart equipment. In this paper, application of Internet of Things (IoT) technology in different parts of the microgrid is carried out to achieve an effective IoT architecture in addition to proposing the Internet-of-Asset (IoA) concept that will be able to convert any legacy asset into a smart IoT-ready one. This will allow the effective connection of all assets to a cloud-based IoT. The role of which is to perform computations and big data analysis on the collected data from across the smart microgrid to send effective energy management and control commands to different controllers. Then the IoT cloud will send control actions to solve microgrid's technical issues such as solving energy mismatch problem by setting prediction models, increasing power quality by the effective commitment of DERs and eliminating load shedding by turning off only unnecessary loads so consumers won't suffer from power outages. The benefits of using IoT on various parts within the microgrid are also addressed.

Dans le cloud computing, les services et les ressources sont centralisés dans des centres de données auxquels l’utilisateur peut accéder à partir de ses appareils connectés. L’infrastructure cloud traditionnelle sera confrontée à une série de défis en raison de la centralisation de calcul, du stockage et de la mise en réseau dans un petit nombre de centres de données, et de la longue distance entre les appareils connectés et les centres de données distants. Pour répondre à ce besoin, l’edge computing s’appuie sur un modèle dans lequel les ressources de calcul sont distribuées dans le edge de réseau selon les besoins, tout en décentralisant le traitement des données du cloud vers le edge autant que possible. Ainsi, il est possible d’avoir rapidement des informations exploitables basées sur des données qui varient dans le temps. Dans cette thèse, nous proposons de nouveaux modèles d’optimisation pour optimiser l’utilisation des ressources dans le edge de réseau pour deux domaines de recherche de l’edge computing, le "service offloading" et "vehicular edge computing". Nous étudions différents cas d’utilisation dans chaque domaine de recherche. Pour les solutions optimales, Premièrement, pour le "service offloading", nous proposons des algorithmes optimaux pour le placement des services dans les serveurs edge (Tasks, Virtual Network Functions (VNF), Service Function Chain (SFC)) en tenant compte des contraintes de ressources de calcul. De plus, pour "vehicular edge computing", nous proposons des modèles exacts liés à la maximisation de la couverture des véhicules par les taxis et les Unmanned Aerial Vehicle (UAV) pour les applications de streaming vidéo en ligne. De plus, nous proposons un edge- autopilot VNFs offloading dans le edge de réseau pour la conduite autonome. Les résultats de l’évaluation montrent l’efficacité des algorithmes proposés dans les réseaux avec un nombre limité d’appareils en termes de temps, de coût et d’utilisation des ressources. Pour faire face aux réseaux denses avec un nombre élevé d’appareils et des problèmes d’évolutivité, nous proposons des algorithmes à grande échelle qui prennent en charge une énorme quantité d’appareils, de données et de demandes d’utilisateurs. Des algorithmes heuristiques sont proposés pour l’orchestration SFC, couverture maximale des serveurs edge mobiles (véhicules). De plus, les algorithmes d’intelligence artificielle (apprentissage automatique, apprentissage en profondeur et apprentissage par renforcement en profondeur) sont utilisés pour le placement des "5G VNF slices", le placement des "VNF-autopilot" et la navigation autonome des drones. Les résultats numériques donnent de bons résultats par rapport aux algorithmes exacts avec haute efficacité en temps
Traditional cloud infrastructure will face a series of challenges due to the centralization of computing, storage, and networking in a small number of data centers, and the long-distance between connected devices and remote data centers. To meet this challenge, edge computing seems to be a promising possibility that provides resources closer to IoT devices. In the cloud computing model, compute resources and services are often centralized in large data centers that end-users access from the network. This model has an important economic value and more efficient resource-sharing capabilities. New forms of end-user experience such as the Internet of Things require computing resources near to the end-user devices at the network edge. To meet this need, edge computing relies on a model in which computing resources are distributed to the edge of a network as needed, while decentralizing the data processing from the cloud to the edge as possible. Thus, it is possible to quickly have actionable information based on data that varies over time. In this thesis, we propose novel optimization models to optimize the resource utilization at the network edge for two edge computing research directions, service offloading and vehicular edge computing. We study different use cases in each research direction. For the optimal solutions, First, for service offloading we propose optimal algorithms for services placement at the network edge (Tasks, Virtual Network Functions (VNF), Service Function Chain (SFC)) by taking into account the computing resources constraints. Moreover, for vehicular edge computing, we propose exact models related to maximizing the coverage of vehicles by both Taxis and Unmanned Aerial Vehicle (UAV) for online video streaming applications. In addition, we propose optimal edge-autopilot VNFs offloading at the network edge for autonomous driving. The evaluation results show the efficiency of the proposed algorithms in small-scale networks in terms of time, cost, and resource utilization. To deal with dense networks with a high number of devices and scalability issues, we propose large-scale algorithms that support a huge amount of devices, data, and users requests. Heuristic algorithms are proposed for SFC orchestration, maximum coverage of mobile edge servers (vehicles). Moreover, The artificial intelligence algorithms (machine learning, deep learning, and deep reinforcement learning) are used for 5G VNF slices placement, edge-autopilot VNF placement, and autonomous UAV navigation. The numerical results give good results compared with exact algorithms with high efficiency in terms of time

The Internet of Things (IoT) concept has been realised with the advent of Machineto-Machine (M2M) communication through which the vision of future Internet has been revolutionised. IPv6 over Low power Wireless Personal Area Networks (6LoWPAN) provides feasible IPv6 connectivity to previously isolated environments, e.g. wireless M2M sensors and actuator networks. This thesis's contributions include a novel mathematical model, energy-efficient algorithms, and a centralised software controller for dynamic consolidation of programmability features in cloud-based M2M networks. A new generalised joint mathematical model has been proposed for performance analysis of the 6LoWPAN MAC and PHY layers. The proposed model differs from existing analytical models as it precisely adopts the 6LoWPAN specifications introduced by the Internet Engineering Task Force (IETF) working group. The proposed approach is based on Markov chain modelling and validated through Monte-Carlo simulation. In addition, an intelligent mechanism has been proposed for optimal 6LoWPAN MAC layer parameters set selection. The proposed mechanism depends on Artificial Neural Network (ANN), Genetic Algorithm (GA), and Particles Swarm Optimisation (PSO). Simulation results show that utilising the optimal MAC parameters improve the 6LoWPAN network throughput by 52-63% and reduce end-to-end delay by 54-65%. This thesis focuses on energy-efficient data extraction and dissemination in a wireless M2M sensor network based on 6LoWPAN. A new scalable and self-organised clustering technique with a smart sleep scheduler has been proposed for prolonging M2M network's lifetime and enhancing network connectivity. These solutions succeed in overcoming performance degradation and unbalanced energy consumption problems in homogeneous and heterogeneous sensor networks. Simulation results show that by adopting the proposed schemes in multiple mobile sink sensory field will improve the total aggregated packets by 38-167% and extend network lifetime by 30-78%. Proof-of-concept real-time hardware testbed experiments are used to verify the effectiveness of Software-Defined Networking (SDN), Network Function Virtualisation (NFV) and cloud computing on a 6LoWPAN network. The implemented testbed is based on open standards development boards (i.e. Arduino), with one sink, which is the M2M 6LoWPAN gateway, where the network coordinator and the customised SDN controller operated. Experimental results indicate that the proposed approach reduces network discovery time by 60% and extends the node lifetime by 65% in comparison with the traditional 6LoWPAN network. Finally, the thesis is concluded with an overall picture of the research conducted and some suggestions for future work.

Varje dag kopplas tusentals godsvagnar om på de olika rangerbangårdarna i Sverige. För att kunna automatiskt bromsa vagnarna tillräckligt mycket är det nödvändigt att veta deras hastigheter. En teknik som har blivit populär på sistone är Light Detection and Ranging (LiDAR) som använder ljus för att mäta avstånd till objekt. Den här rapporten diskuterar design- och implementationsprocessen av ett trådlöst sensornätverk bestående av en LiDARutrustad sensornod. Designprocessen gav en insikt i hur LiDAR-sensorer bör placeras för att täcka en så stor yta som möjligt. Sensornoden var programmerad att bestämma avståndet av objekt genom att använda Random Sample Consensus (RANSAC) för att ta bort outliers och sen linjär regression på de inliers som detekterats. Implementationen utvärderades genom att bygga ett litet spår med en låda som kunde glida fram och tillbaka över spåret. LiDAR- sensorn placerades med en vinkel vid sidan om spåret. Resultaten visade att implementationen både kunde detektera objekt på spåret och också hastigheten av objekten. En simulation gjordes också med hjälp av en 3D-modell av en tågvagn för att se hur väl algoritmen hanterade ojämna ytor. LiDAR-sensorn i simuleringen hade en strålavvikelse på 0_. 30% av de simulerade mätvärdena gjordes om till outliers för att replikera dåliga väderförhållanden. Resultaten visade att RANSAC effektivt kunde ta bort outliers men att de ojämna ytorna på tåget ledde till felaktiga hastighetsmätningar. En slutsats var att en sensor med en divergerande stråle möjligtvis skulle leda till bättre resultat. Framtida arbete inkluderar att utvärdera implementationen på en riktig bangård, hitta optimala parametrar för algoritmen samt evaluera algoritmer som kan filtrera data från ojämn geometri.
Every day, thousands of train wagons are coupled on the multiple classification yards in Sweden. To be able to automatically brake the wagons a sufficient amount, it is a necessity to determine the speed of the wagons. A technology that has been on the rise recently is Light Detection and Ranging (LiDAR) that emits light to determine the distance to objects. This report discusses the design and implementation of a wireless sensor network consisting of a LiDAR-equipped sensor node. The design process provided insight into how LiDAR sensors may be placed for maximum utilization. The sensor node was programmed to determine the speed of an object by first using Random Sample Consensus (RANSAC) for outlier removal and then linear regression on the inliers. The implementation was evaluated by building a small track with an object sliding over it and placing the sensor node at an angle to the side of the track. The results showed that the implementation could both detect objects on the track and also track the speed of the objects. A simulation was also made using a 3D model of a wagon to see how the algorithm performs on non-smooth surfaces. The simulated LiDAR sensor had a beam divergence of 0_. 30% of the simulated measurements were turned into outliers to replicate bad weather conditions. The results showed that RANSAC was efficient at removing the outliers but that the rough surface of the wagon resulted in some incorrect speed measurements. A conclusion was made that a sensor with some beam divergence could be beneficial. Future work includes testing the implementation in real-world scenarios, finding optimal parameters for the proposed algorithm, and to evaluate algorithms that can filter rough geometry data.

Il presente lavoro ha come obiettivo proporre un'analisi di una delle tecnologie emersa negli ultimi anni: LoRaWAN, "Long Range Wide Area Network". In particolare l'obiettivo è testare le prestazioni nella trasmissione dei nodi LoRa a brevi distanze in ambienti indoor/outdoor attraverso un server della rete The Thing Network e sperimentare il servizio offerto dalla rete IoT Lepida della pubblica amministrazione della regione Emilia Romagna. Nel capitolo 2 viene descritta la tecnologia LoRaWAN e per quale motivo si presta bene ad implementare delle reti IoT. In particolare si analizza la struttura della rete attraverso lo stack tecnologico soffermandosi sulla modulazione LoRa (layer �fisico) e sullo strato MAC. Viene in�ne illustrata l'architettura della rete implementata che mette in comunicazione un End Device con The Thing Network e Lepida. Nel capitolo 3 viene presentata la Rete Lepida, ed attraverso la sperimentazione del suo servizio di rete IoT, viene descritto come è possibile registrare un nodo personale, specificando quali sono i tipi di connessione e le relative chiavi necessarie. In seguito vengono esposti i vari tipi di visualizzazione dati che il servizio mette a disposizione dell'utente. Nel capitolo 4 viene utilizzata la rete The Thing Network per mappare la copertura dell'intera zona del campus di Cesena e veri�care la connettività di un nodo LoRa con un Gateway privato presente in sede. Nel Capitolo conclusivo vengono esposte le considerazioni fatte in luce della sperimentazione di un servizio IoT, e delle potenzialità di LoRaWAN in generale.

Radiofrequency spectrum is a finite resource that consists of the frequencies in the range 3 kHz to 300 GHz. It is used for wireless communication and supports several applications and services. Whether it is at the personal, community or society level, and whether it is for applications in consumer electronics, building management, smart utility networks, intelligent driving systems, the Internet of Things, industrial automation and so on, the demand for wireless communication is increasing continuously. Together with this increase in demand, there is an increase in the quality of service requirements in terms of throughput, and the reliability and availability of wireless services. Industrial wireless sensor networks, for example, operate in environments that are usually harsh and time varying. The frequency spectrum that is utilised by industrial wireless protocols such as WirelessHART and ISA 100.11a, is also used by many other wireless technologies, and with wireless applications growing rapidly, it is possible that multiple heterogeneous wireless systems will need to operate in overlapping spatiotemporal regions in the future. Increased radiofrequency interference affects connectivity and reduces communication link quality. This affects reliability and latency negatively, both of which are core quality service requirements. Getting multiple heterogeneous radio systems to co-exist harmoniously in shared spectrum is challenging. Traditionally, this has been achieved by granting network operators exclusive rights that allow them to access parts of the spectrum assigned to them and hence the problems of co-existence and limited spectrum could be ignored. Design time multi-access techniques have also been used. At present, however, it has become necessary to use spectrum more efficiently, to facilitate the further growth of wireless communication. This can be achieved in a number of ways. Firstly, the policy that governs the regulation of radiofrequency spectrum must be updated to accommodate flexible, dynamic spectrum access. Secondly, new techniques for multiple-access and spectrum sharing should be devised. A revolutionary new communication paradigm is required, and one such paradigm has recently emerged in the form of Cognitive Radio technology. Traditional methods to sharing spectrum assume that radios in a wireless network work together in an unchanging environment. Cognitive radios, on the other hand, can sense, learn and adapt. In cognitive radio networks, the interactions between users are taken into account, in order for adjustments to be made to suit the prevailing radio environment. In this thesis, the problem of spectrum scarcity and coexistence is addressed using cognitive radio techniques, to ensure more efficient use of radio-frequency spectrum. An introduction to cognitive radio networks is given, covering cognitive radio fundamentals, spectrum sensing, dynamic spectrum management, game theoretic approaches to spectrum sharing and security in cognitive radio networks. A focus is placed on wireless industrial networks as a challenging test case for cognitive radio. A study on spectrum management policy is conducted, together with an investigation into the current state of radio-frequency spectrum utilisation, to uncover real and artificial cases of spectrum scarcity. A novel cognitive radio protocol is developed together with an open source test bed for it. Finally, a game theoretic dynamic spectrum access algorithm is developed that can provide scalable, fast convergence spectrum sharing in cognitive radio networks. This work is a humble contribution to the advancement of wireless communication.
Thesis (PhD)--University of Pretoria, 2016.
Centre for Telecommunication Engineering for the Information Society
Electrical, Electronic and Computer Engineering
PhD
Unrestricted

Durant cette dernière décennie, plusieurs objets connectés tels que les ordinateurs, les capteurs et les montres intelligentes ont intégrés notre quotidien et forment aujourd’hui ce que l’on appelle l’Internet des Objets (IdO) ou Internet of Things (IoT) en anglais. L’IoT est un nouveau paradigme permettant une interaction entre les objets connectés afin d’améliorer notre qualité de vie, notre façon de produire des biens et notre façon d’interagir avec notre environnement. De nos jours, l’IoT se caractérise par la présence, de par le monde, de milliards d’objets connectés à faibles ressources (batterie, mémoire, CPU, bande passante disponible, etc) et hétérogènes, déployés pour permettre diverses applications couvrant de nombreux domaines de notre société tels que la santé, l’industrie, les transports, l’agriculture, etc. Cependant, en raison des contraintes lié aux ressources et de l’hétérogénéité des objets connectés, les réseaux IoT à faibles ressources présents font face à des problèmes de performance, notamment la dégradation de la qualité des liens radio, la défaillance (logicielle ou matérielle) de certains objets du réseau, la congestion du réseau, etc. Ainsi, il est donc important de gérer efficacement les réseaux IoT à faible ressources afin d’assurer leur bon fonctionnement. Pour ce faire, la solution de gestion du réseau doit être autonome (pour faire face à la nature dynamique des réseaux IoT), tenir compte de l’hétérogénéité des objets connectés et être moins consommatrice en énergie pour répondre aux défis de l’IoT. Dans cette thèse, nous nous sommes intéressés au problème de gestion des réseaux IoT à faibles ressources et avons proposés des solutions efficaces pour permettre une optimisation des performances de ces types de réseaux. Dans un premier temps nous avons procédé à une étude comparative des solutions de gestion des réseaux IoT à faibles ressources afin d’identifier les verrous techniques. Ensuite, nous avons proposé une solution intelligente qui se base sur un modèle de réseau de neurones profonds pour permettre une configuration de la portée radio dans les réseaux sans fil à faibles ressources de type RPL (IPv6 Routing Protocol for Low power and Lossy Networks). Une évaluation des performances de cette solution montre qu’elle est capable de déterminer la portée radio permettant une réduction de la consommation énergétique du réseau tout en garantissant une connectivité des objets connectés. Nous avons également proposé une solution efficace et adaptative pour configurer les paramètres de la couche MAC dans les réseaux dynamiques de type IEEE 802.15.4. Les résultats des simulations démontrent que notre solution améliore le délai de transmission bout en bout par rapport à l’utilisation des paramètres par défaut de la MAC IEEE 802.15.4. En outre, nous avons proposé une étude des solutions existante pour la gestion des problèmes de congestion des réseaux IoT à faibles ressources et par la suite nous avons proposé un procédé d’acheminement de l’information de congestion des objets connectés présents sur un chemin de routage donné dans des réseaux à ressources limitées. Cette méthode a pour but de permettre une réponse efficace aux problèmes de congestion
In these recent years, several connected objects such as computer, sensors and smart watches became part of modern living and form the Internet of Things (IoT). The basic idea of IoT is to enable interaction among connected objects in order to achieve a desirable goal. IoT paradigm spans across many areas of our daily life such as smart transportation, smart city, smart agriculture, smart factory and so forth. Nowadays, IoT networks are characterized by the presence of billions of heterogeneous embedded devices with limited resources (e.g. limited memory, battery, CPU and bandwidth) deployed to enable various IoT applications. However, due to both resource constraints and the heterogeneity of IoT devices, IoT networks are facing with various problems (e.g. link quality deterioration, node failure, network congestion, etc.). Considering that, it is therefore important to perform an efficient management of IoT low power networks in order to ensure good performance of those networks. To achieve this, the network management solution should be able to perform self-configuration of devices to cope with the complexity introduced by current IoT networks (due to the increasing number of IoT devices and the dynamic nature of IoT networks). Moreover, the network management should provide a mechanism to deal with the heterogeneity of the IoT ecosystem and it should also be energy efficient in order to prolong the operational time of IoT devices in case they are using batteries. Thereby, in this thesis we addressed the problem of configuration of IoT low power networks by proposing efficient solutions that help to optimize the performance of IoT networks. We started by providing a comparative analysis of existing solutions for the management of IoT low power networks. Then we propose an intelligent solution that uses a deep neural network model to determine the efficient transmission power of RPL networks. The performance evaluation shows that the proposed solution enables the configuration of the transmission range that allows a reduction of the network energy consumption while maintaining the network connectivity. Besides, we also propose an efficient and adaptative solution for configuring the IEEE 802.15.4 MAC parameters of devices in dynamic IoT low power networks. Simulation results show that our proposal improves the end-to-end delay compared to the usage of the standard IEEE 802.15.4 MAC. Additionally, we develop a study on solutions for congestion control in IoT low power networks and propose a novel scheme for collecting the congestion state of devices in a given routing path of an IoT network so as to enable an efficient mitigation of the congestion by the network manager (the device in charge of configuration of the IoT network)

The current network trends point towards a significant discrepancy between the data usage and the underlying architecture; a severely increasing amount of data is being sent from more devices while data usage is becoming more data-centric instead of the previously host-centric. Information Centric Network (ICN) is a new alternative network paradigm that is designed for a data-centric usage. ICN is based on uniquely naming data packages and making it location independent. This thesis researched how to implement an efficient naming for ICN in a Smart Home Scenario. The results are based on testing how the forwarding information base is populated for numerous different scenarios and how a node's duty cycle affects its power usage. The results indicate that a hierarchical naming is optimized for hierarchical-like network topology and a flat naming for interconnected network topologies. An optimized duty cycle is strongly dependent on the specific network and accordingto the results can a sub-optimal duty cycle lead to excessive powerusage.

This thesis was carried out in the context of a project developed by the university of Bologna upon commission of GD SpA, aimed at providing a new proprietary solution for a Industrial Internet of Things monitoring application. The focus is on the definition and implementation of a wireless communication protocol, which has been called LoRaIN, based on LoRa technology at 2,4 GHz and suitable for Industry 4.0 applications. LoraIN proposes a centralized approach to Network management, with a single entity keeping synchronization among devices and scheduling all the transmissions according to separated time slots, in order to avoid collisions. Distinctive features of the protocol are also its multi-hopping functionality and the possibility to deploy batteryless devices, charged via Wireless Power Transfer technology. Numerical results reported in the thesis demonstrate how LoRaIN protocol meets the application requirements.

Embedded systems have been present in our daily lives for some time, but trends clearly show a rise in inter-connectivity in such devices. This presents promising new applications and possibilities, but also opens up a lot attack surface. Our goal in this thesis is to find out how you can develop such interconnected embedded systems in a way that guarantees the three major components of information security: Confidentialy, Integrity and Availability. The main focus of security is networked security. In this thesis, a dual approach is taken: investigate the development process of building secure systems, and perform such an implementation. The artifacts produced as byproducts, the software itself, deployment instructions and lessons learned are all presented. It is shown that the process used helps businesses find a somewhat deterministic approach to security, have a higher level of confidence, helps justify the costs that security work entails and helps in seeing security as a business decision. Embedded systems were also shown to present unforeseen obstacles, such as how the lack of a motherboard battery clashes with X.509. In the end, a discussion is made about how far the system can guarantee information security, what problems still exist and what could be done to mitigate them.

In conjunction with the possibility of inexpensive wireless communication, many products of tomorrow are developed with the support for wireless communication. The technology enables the possibilty of wireless communication to small plattforms at a realistic price. The cheap connectivity allows for great creativity and gives the developers imagination a wide discretion in the development of new products. This thesis aims to evaluate how the serial communication protocol Modbus RTU - RS232, performs and behaves when transported through meshed networks (Atmel lightweight mesh will be used in this thesis). The work was commissioned by M2M Solutions in J¨onk¨oping. The report will answer the following questions1. How does Modbus RTU behaves when transported through a meshed network. 2. How does Modbus RTU preform when transported through Atmel Lightweight Mesh.The authors have chosen to conduct action research to answer established questions. A test system consisting of both hardware and software was designed and created. With this system, several different tests were conducted and the results were observed and subjected to reflection. The different tests varied the distance, the network’s composition and location of the network infrastructure. Through observation of the test system and evaluation of the recorded data conclusions concering Modbus RTU’s performance and behavior during transport in Atmel lightweigh mesh has been drawn. The test system has been designed with the help of clients and previously made research. Modbus behaves nominally during transportation through Atmel lightweight mesh. Before the network is fully established, an inability to transport data has beend observed. The performance is evaluated by the time it takes to send data, the time is greatly affected by the following factors; Network composition and changes in signal strength (that creates changes in transport routes). For each additional node that traffic is transported through an increase of 5-10ms in the responstime was noted. The network’s ability to change the transport route is also expected to increase performance. The wireless communication provides a longer range than during transportation by standard conventional cable.Considering the results, the authors believe that Modbus RTU has the potential for use in transportation through wireless, meshed networks. One possible scenario is when several Modbus RTU masters are beeing used and data needs to be transported over large distances.

Récemment, l'intégration entre les environnements informatiques et de réseautage a été largement promu pour fournir des services intelligents à des utilisateurs finaux ainsi que l'utilisation efficace des ressources. Cette convergence a ouvert la voie à l'émergence de l'internet des objets (IdO). Le paradigme de l'IdO repose principalement sur la fabrication d'objets, appelés les choses, disparaître et se tissent dans le tissu de notre vie de tous les jours pour nous soutenir dans l'accomplissement des activités quotidiennes. L'évolutivité et l'hétérogénéité sont parmi les principaux défis qui entravent la réalisation à grande échelle de services de l'IdO dans la vie quotidienne des utilisateurs. Afin de relever les défis de l'IdO, un nouveau volet de recherche est venu en avant dans la littérature comme une classe paradigmatique des Cyber-physiques systèmes sociaux (CSPR), qui est connu comme l'Internet social des choses (Siot). Le SIOT se fonde sur la notion soulignée par phénomène petite-monde où la structure sociale permettant relation sociale fondée sur la confiance entre les personnes et les objets, d'une manière qui ressemble à des services de réseaux sociaux traditionnels (SNS) est suggérée de relever les défis de l'IdO. Cependant, depuis SIOT hérite des caractéristiques de différents informatiques et de réseautage environnements (par exemple, l'IdO et SNS) cela, en fait, augmente la quantité et la variété des données contextuelles qui doit être manipulé pour Adaptive fourniture de services dans Siot, qui agit comme le principal défi adressé dans cette thèse. Autrement dit, dans cette thèse, nous proposons la notion de contexte cognitif lorsque, dans certaine situation spatio-temporelle, le raisonnement sur les aspects objectifs du cadre, ce qui représente l'environnement physique, avec le contexte subjective, qui représente les aspects comportementaux et sociaux, est considéré comme l'amélioration des services SIOT intelligence et la capacité d'adaptation aux besoins conjoncturels des utilisateurs. Nous envisageons technologies du Web sémantique pour déployer notre contexte cognitif proposé dans deux domaines d'application; sensible au contexte recommandation des tâches quotidiennes dans les maisons intelligentes et structure sociale dépendant de la situation des choses. Un prototype de preuve de concept a été développé pour chaque domaine d'application, dans le but de démontrer l'intégration harmonieuse des objets sur le Web pour la réalisation de certaines applications. Nos résultats empiriques montrent un niveau de service amélioré l'adaptabilité et la complexité en temps de fonctionner lors de l'application de notre contexte cognitif suggéré
The paradigm of the Social Internet of Things (SIoT) is being promoted in the literature to boost a new trend wherein the benefits of social network services are exhibited within the network of connected objects i.e., the Internet of Things (IoT). The novel user-friendly interaction framework of the SIoT opens the doors for enhancing the intelligence required to stimulate a shift in the IoT from a heterogeneous network of independently connected objects towards a manageable network of everything. In practice, achieving scalability within the large-scale and the heterogeneous paradigm of the IoT while maintaining on top of its user-friendly and intuitive services to bridge human-to-machine perceptions and encourage the technology’s adaptation is a major challenge which is hindering the realization and deployment of the IoT technologies and applications into people’s daily live. For the goal of handling IoT challenges, as well as improve the level of smart services adaptability to users’ situational needs, in this thesis, novel SIoT-based application architecture is provided. That is, Semantic Web Technologies are envisaged as a means to develop automated, value-added services for SIoT. While, interoperability and automation are essential requirement to seamlessly integrate such services into user life, Ontologies are used to semantically describe Web services with the aim of enabling the automatic invocation and composition of these services as well as support interactions across the cyber, physical and social worlds. On the other hand, handling the variety of contextual data in SIoT for intelligent decision making is another big challenge which is still in very early stages of research. In this thesis we propose a cognitive reasoning approach taking into consideration achieving situational-awareness (SA) in SIoT. This reasoning approach is deployed within two application domains where results show an improved level of services adaptability compared to location-aware services which are previously proposed in the literature

La compagnie Sigfox est reconnue comme un acteur prometteur pour des transmissions de longue-distance et faible consommation, dans le contexte de l'IoT. La modulation à bande ultra étroite (Ultra Narrow Band (UNB)), la technologie de communication choisie par Sigfox, permet de transmettre des informations dans des bandes de signal très étroites (typiquement 100 Hz). A cause de l'imprécision fréquentielle causée par les oscillateurs générateurs de fréquence, il n'est pas réaliste de transmettre des signaux UNB dans des canaux parfaitement orthogonaux. L'accès naturel au canal radio pour le système de UNB est de type ALOHA, avec un aspect aléatoire à la fois en en temps et en fréquence. Cet accès aléatoire peut introduire des collisions qui dégradent la performance du réseau. Le but de cette thèse est de caractériser la capacité des réseaux basés sur UNB, ainsi que d’améliorer la performance en considérant l'aspect aléatoire en temps et en fréquence. La première contribution de cette thèse, est une évaluation de la capacité en théorie et en simulation pour une seule station de base (BS), sous des conditions de canal idéaliste ou réaliste. En conditions idéalistes, nous avons exprimé la capacité pour le cas de l'ALOHA généralisé, et l'avons étendu aux cas de réplications. Pour les conditions réalistes, nous avons pris en compte l'interférence spectrale d'UNB et le path loss (sans et avec Rayleigh fading) afin de caractériser la performance des réseaux UNB, avec l'outil géométrie stochastique. La deuxième contribution est d'appliquer l’annulation successive d'interférence (SIC), qui nous permet d'atténuer les interférences, dans des réseaux de UNB. Nous avons fourni une analyse théorique de la performance des réseaux en considérant le SIC et l'interférence spectrale de UNB, pour le cas de mono-BS. La troisième contribution est l'amélioration de la performance des réseaux UNB, en exploitant la diversité de multi-BS. Nous avons fait une analyse théorique de performance en considérant multi-BS et selection combining (SC). En particulier, nous avons considéré que l’interférence vue par chaque BS est corrélée. Nous avons ainsi démontré mathématiquement que cette corrélation ne peut pas être supprimée dans des systèmes UNB. Ensuite, nous avons appliqué les technologies de la combinaison des signaux plus complexes comme MRC (max ratio combining) et EGC (equal gain combining), ainsi que le SIC à travers multi-BS. Nous avons évalué l'amélioration de performance que chaque technologie apporte, et les avons comparées. Nous avons souligné l'efficacité de ces technologies qui nous permettent d’obtenir des gains importants comparés au cas mono-BS (e.x. 125 fois plus de réduction d'erreur avec SIC globale). La dernière contribution est une validation expérimentale du modèle d'interférence spectrale de UNB, ainsi que la capacité des réseaux UNB, sur un testbed de radio FIT/Cortexlab
Sigfox rises as a promising candidate dedicated for long-distance and low-power transmissions in the IoT backgrounds. Ultra Narrow Band (UNB), being the communication technology chosen by Sigfox, allows to transmit information through signals whose bandwidth is very limited, typically 100 Hz. Due to the imprecision restraint on electronic devices, it is impossible to transmit UNB signals in orthogonal channels. The natural radio access for this kind of system is thus random ALOHA, in both time and frequency domain. This random access can induce collisions which degrades the networks performance. The aim of this thesis is to characterize the capacity of UNB based networks, as well as to enhance its performance, by considering the randomness in time and frequency. The first contribution of the thesis, is the theoretical and numerical capacity evaluation under idealized and realistic channel conditions, for mono base station (BS) case. Under idealized conditions, we have quantified this capacity for generalized ALOHA case and extended for replications. We highlight the time-frequency duality in UNB systems, and that there exists an optimum replication number for a given network parameter set. Under realistic conditions, we have taken into account the specific spectral interference of UNB systems and propagation path loss (without and with Rayleigh fading) to characterize the performance, with the aid of stochastic geometry. The second contribution is the enhancement of UNB network performance in single BS case. We propose to use successive interference cancellation (SIC) in UNB networks, which allows to mitigate the interference. We have provided a theoretical analysis by considering both SIC and the spectral interference, for mono-BS case. We bring to light the efficiency of SIC in enhancing UNB system performance. The third contribution is the improvement of UNB systems, by exploiting the multiple BS diversity. An analytical performance evaluation considering the simplest selection combining is conducted. In particular, we consider the interference viewed by all the BSs are correlated. Then we apply more complex signal combining technologies such as MRC (max ratio combining) and EGC (equal gain combining), and even interference cancellation across multi-BS in UNB networks. We evaluate the performance improvement that each technology can bring, and compare them with each other. We highlight the efficiency of these multi-BS technologies which allow us to achieve significant performance enhancement compared to mono-BS (e.x. 125 times better performance with global SIC). Last but not least, we experimentally verify the the spectral interference model and network capacity on a cognitive radio testbed

Nowadays it is more clear that the Internet of things (IoT) is not a transient trend but a completely new industry. The internet of things has the capability to enhance current industries (Industry 4.0), as well as to help protecting the environment and people. The latter is the case with the system developed and described in this thesis. The possibilities that IoT brings are due to the interconnection of heterogeneous embedded devices to the internet. This thesis focus on LPWANs (Low Power Wide Area Networks), which is a new set of technologies specifically design for the needs of IoT devices.Due to the recent deploy of NB-IoT (Narrow Band IoT) networks it has become more difficult to know what LPWAN is best for a certain application. Thus, the first half of this thesis involves the comparative study of NB-IoT and LoRaWAN LPWANs. This comparison required an in depth study of each technology, specially on the physical and datalink layers. The comparison briefly displays the main characteristics of each technology and explain the main conclusions in a concise manner. The second part of the thesis describes the development of a GNSS tracker. This tracker will be used on train wagons carrying goods that are dangerous for people and the environment. This thesis report describes the different steps taken, from the requirement specification to the partial development of the software.

Récemment, l'intégration entre les environnements informatiques et de réseautage a été largement promu pour fournir des services intelligents à des utilisateurs finaux ainsi que l'utilisation efficace des ressources. Cette convergence a ouvert la voie à l'émergence de l'internet des objets (IdO). Le paradigme de l'IdO repose principalement sur la fabrication d'objets, appelés les choses, disparaître et se tissent dans le tissu de notre vie de tous les jours pour nous soutenir dans l'accomplissement des activités quotidiennes. L'évolutivité et l'hétérogénéité sont parmi les principaux défis qui entravent la réalisation à grande échelle de services de l'IdO dans la vie quotidienne des utilisateurs. Afin de relever les défis de l'IdO, un nouveau volet de recherche est venu en avant dans la littérature comme une classe paradigmatique des Cyber-physiques systèmes sociaux (CSPR), qui est connu comme l'Internet social des choses (Siot). Le SIOT se fonde sur la notion soulignée par phénomène petite-monde où la structure sociale permettant relation sociale fondée sur la confiance entre les personnes et les objets, d'une manière qui ressemble à des services de réseaux sociaux traditionnels (SNS) est suggérée de relever les défis de l'IdO. Cependant, depuis SIOT hérite des caractéristiques de différents informatiques et de réseautage environnements (par exemple, l'IdO et SNS) cela, en fait, augmente la quantité et la variété des données contextuelles qui doit être manipulé pour Adaptive fourniture de services dans Siot, qui agit comme le principal défi adressé dans cette thèse. Autrement dit, dans cette thèse, nous proposons la notion de contexte cognitif lorsque, dans certaine situation spatio-temporelle, le raisonnement sur les aspects objectifs du cadre, ce qui représente l'environnement physique, avec le contexte subjective, qui représente les aspects comportementaux et sociaux, est considéré comme l'amélioration des services SIOT intelligence et la capacité d'adaptation aux besoins conjoncturels des utilisateurs. Nous envisageons technologies du Web sémantique pour déployer notre contexte cognitif proposé dans deux domaines d'application; sensible au contexte recommandation des tâches quotidiennes dans les maisons intelligentes et structure sociale dépendant de la situation des choses. Un prototype de preuve de concept a été développé pour chaque domaine d'application, dans le but de démontrer l'intégration harmonieuse des objets sur le Web pour la réalisation de certaines applications. Nos résultats empiriques montrent un niveau de service amélioré l'adaptabilité et la complexité en temps de fonctionner lors de l'application de notre contexte cognitif suggéré
The paradigm of the Social Internet of Things (SIoT) is being promoted in the literature to boost a new trend wherein the benefits of social network services are exhibited within the network of connected objects i.e., the Internet of Things (IoT). The novel user-friendly interaction framework of the SIoT opens the doors for enhancing the intelligence required to stimulate a shift in the IoT from a heterogeneous network of independently connected objects towards a manageable network of everything. In practice, achieving scalability within the large-scale and the heterogeneous paradigm of the IoT while maintaining on top of its user-friendly and intuitive services to bridge human-to-machine perceptions and encourage the technology’s adaptation is a major challenge which is hindering the realization and deployment of the IoT technologies and applications into people’s daily live. For the goal of handling IoT challenges, as well as improve the level of smart services adaptability to users’ situational needs, in this thesis, novel SIoT-based application architecture is provided. That is, Semantic Web Technologies are envisaged as a means to develop automated, value-added services for SIoT. While, interoperability and automation are essential requirement to seamlessly integrate such services into user life, Ontologies are used to semantically describe Web services with the aim of enabling the automatic invocation and composition of these services as well as support interactions across the cyber, physical and social worlds. On the other hand, handling the variety of contextual data in SIoT for intelligent decision making is another big challenge which is still in very early stages of research. In this thesis we propose a cognitive reasoning approach taking into consideration achieving situational-awareness (SA) in SIoT. This reasoning approach is deployed within two application domains where results show an improved level of services adaptability compared to location-aware services which are previously proposed in the literature

The Internet of Things (IoT) is an umbrella term for smart things connected to the Internet. Connected sensors may be used to the benefit of smart building management systems. This thesis describes the development of a sensor based building management system prototype, lightweight enough to run on a single network camera. The focus of the research was investigating if the system prototype was scalable, and capable of storing and analyzing data gathered from a large amount of sensors relevant to the field of building management. The prototype was developed through a five-stage systems development process, and evaluated using simulations and case studies. The finished prototype was able to gather and store data from a few hundred real-time sensors using limited hardware. Tests showed that the network camera should be capable of managing at least 100 sensors. The system itself is scalable with the use of more powerful hardware. However, using a distributed architecture would be preferable if more sensors are required. This could be achieved by creating a distributed network of cameras, where each camera manages its own set of sensors. This could both increase scalability and make the system more robust and reliable.

Flood disasters affect millions of people across the world by causing severe loss of life and colossal damage to property. Internet of things (IoT) has been applied in areas such as flood prediction, flood monitoring, flood detection, etc. Although IoT technologies cannot stop the occurrence of flood disasters, they are exceptionally valuable apparatus for conveyance of catastrophe readiness and counteractive action data. Advances have been made in flood prediction using artificial neural networks (ANN). Despite the various advancements in flood prediction systems through the use of ANN, there has been less focus on the utilisation of edge computing for improved efficiency and reliability of such systems. In this thesis, a system for short-term flood prediction that uses IoT and ANN, where the prediction computation is carried out on a low power edge device is proposed. The system monitors real-time rainfall and water level sensor data and predicts ahead of time flood water levels using long short-term memory. The system can be deployed on battery power as it uses low power IoT devices and communication technology. The results of evaluating a prototype of the system indicate a good performance in terms of flood prediction accuracy and response time. The application of ANN with edge computing will help improve the efficiency of real-time flood early warning systems by bringing the prediction computation close to where data is collected.
Översvämningar drabbar miljontals människor över hela världen genom att orsaka dödsfall och förstöra egendom. Sakernas Internet (IoT) har använts i områden som översvämnings förutsägelse, översvämnings övervakning, översvämning upptäckt, etc. Även om IoT-teknologier inte kan stoppa förekomsten av översvämningar, så är de mycket användbara när det kommer till transport av katastrofberedskap och motverkande handlingsdata. Utveckling har skett när det kommer till att förutspå översvämningar med hjälp av artificiella neuronnät (ANN). Trots de olika framstegen inom system för att förutspå översvämningar genom ANN, så har det varit mindre fokus på användningen av edge computing vilket skulle kunna förbättra effektivitet och tillförlitlighet. I detta examensarbete föreslås ett system för kortsiktig översvämningsförutsägelse genom IoT och ANN, där gissningsberäkningen utförs över en låg effekt edge enhet. Systemet övervakar sensordata från regn och vattennivå i realtid och förutspår översvämningsvattennivåer i förtid genom att använda långt korttidsminne. Systemet kan köras på batteri eftersom det använder låg effekt IoT-enheter och kommunikationsteknik. Resultaten från en utvärdering av en prototyp av systemet indikerar en bra prestanda när det kommer till noggrannhet att förutspå översvämningar och responstid. Användningen av ANN med edge computing kommer att förbättra effektiviteten av tidiga varningssystem för översvämningar i realtid genom att ta gissningsberäkningen närmare till där datan samlas.

L'Internet des Objets ou en anglais the Internet of Things (IoT) représente aujourd'hui une partie majeure de notre vie quotidienne. Des milliards d'objets intelligents et autonomes, à travers le monde sont connectés et communiquent entre eux. Ce paradigme révolutionnaire crée une nouvelle dimension qui enlèveles frontières entre le monde réel et le monde virtuel. Son succès est dû à l’évolution des équipements matériels et des technologies de communication notamment sans fil. L’IoT est le fruit du développement et de la combinaison de différentes technologies. Il englobe presque tous les domaines de la technologie d’information (Information Technology (IT)) actuels.Les réseaux de capteurs sans fil représentent une pièce maîtresse du succès de l'IoT. Car en utilisant des petits objets qui sont généralement limités en terme de capacité de calcul, de mémorisation et en énergie, des environnements industriels, médicaux, agricoles, et autres peuvent être couverts et gérés automatiquement.La grande puissance de l’IoT repose sur le fait que ses objets communiquent, analysent, traitent et gèrent des données d’une manière autonome et sans aucune intervention humaine. Cependant, les problèmes liés à la sécurité freinent considérablement l’évolution et le déploiement rapide de cette haute echnologie. L'usurpation d’identité, le vols d’information et la modification des données représentent un vrai danger pour ce système des systèmes.Le sujet de ma thèse consiste en la création d'un système de sécurité permettant d’assurer les services d’authentification des objets connectés, d’intégrité des données échangées entres ces derniers et de confidentialité des informations. Cette approche doit prendre en considération les contraintes des objets et des technologies de communication utilisées
Internet of Things becomes a part of our everyday lives. Billions of smart and autonomous things around the world are connected and communicate with each other. This revolutionary paradigm creates a new dimension that removes boundaries between the real and the virtual worlds. Its success is due to the evolution of hardware and communication technologies, especially wireless ones. IoT is the result of the development and combination of different technologies. Today, it covers almost all areas of information technology (IT).Wireless sensor networks are a cornerstone of IoT's success. Using constrained things, industrial, medical, agricultural, and other environments can be automatically covered and managed.Things can communicate, analyze, process and manage data without any human intervention. However, security issues prevent the rapid evolution and deployment of this high technology. Identity usurpation, information theft, and data modification represent a real danger for this system of systems.The subject of my thesis is the creation of a security system that provides services for the authentication of connected things, the integrity of their exchanged data and the confidentiality of information. This approach must take into account the things and communication technologies constraints

Secret sharing is critical to most applications making use of security and remains one of the most challenging research areas in modern cryptography. In this thesis, we propose a novel efficient multi-secret sharing scheme based on the Chinese remainder theorem (CRT) with two verification methods, while the previous works are mostly based on the Lagrange polynomial. Key management schemes play an important role in communication security in Wireless Sensor Networks (WSNs). While the previous works mainly targeting on two different types of WSNs: distributed and hieratical, in this thesis, we propose our flexible WSN key management scheme, which is based on (n,t,n) multi-secret sharing technique, to provide a key management solution for heterogeneous architecture. The powerful key managers are responsible for most of the communicational and computational workload. They can provide Peer-to-Peer pair-wise keys for a pair of sensors to establish a secure communication session, and in the same time, they can also form communication clusters as cluster heads according to different application requirements. Internet of Things (IoT) becomes more and more popular and practical in recent years. Considering the diversity of the devices and the application scenarios, it is extremely hard to couple two devices or sub-networks with different communication and computation resources. In this thesis, we propose novel key agreement schemes based on (n,t,n) multi-secret sharing techniques for IoT in order to achieve light weighted key exchange while using Host Identity Protocol (HIP). We refer the new schemes as HIP-MEXs with different underlying multi-secret sharing techniques. We analyzed the computational and communication costs of the extremely resource constrained device which is referred to as Initiator, and CRT based HIP-MEX successfully outsource the heavy workload to the proxy, which are considered more powerful, when establishing new secret key.

Les réseaux « Internet des Objets » se composent de plusieurs millions d’objets qui possèdent une adresse IP et qui peuvent connecter sur Internet. En général, ces objets sont supposé d’être autonomes et peuvent résoudre des tâches; mesurer, traiter et fournir des informations pour les systèmes connectés et pour les utilisateurs. Aussi, ces réseaux sont vulnérables (c.-à-d. : les éléments peuvent être mobiles et la topologie du réseau peut changer dynamiquement), les changements peuvent influencer le (bon) fonctionnement du réseau. De plus, ils peuvent être alimentés par des batteries de durée de vie limitée, ce que nécessite la réduction de leur consommation.Ce travail de thèse aborde un sujet important dans le domaine de l’Internet des Objets, qui consiste à savoir comment assurer la robustesse et le fonctionnement tolérant aux pannes du réseau pour répondre aux exigences des missions critiques. Avec le large déploiement des services IdO, ce problème est deventé ou de détection de pannes et de sécurité industriel où l’état des objets communicants doit être constamment vérifié pour le rétablissement rapide en cas de problème particulièrement crucial pour les applications telles que le monitorage intelligent de sames de communication inattendus. On cherche alors de minimiser le coût du monitorage et l’utilisation de l’énergie, et aussi les charges additionnelles sur les réseaux.Nous avons proposé un algorithme qui vise à réaliser un placement distribué des moniteurs avec une complexité minimale pour le calcul. L’algorithme proposé fonctionne avec RPL. L’objectif principal est d’augmenter la robustesse dans les réseaux IdO ciblant les applications critiques en temps réel via le monitorage des liaisons dans les DODAGs construits par RPL. Dans notre première contribution, le problème est modélisé comme un problème de couverture minimale des sommets (VCP) sur le DODAG. Nous avons développé un algorithme à temps polynomial qui transforme le DODAG en une décomposition arborescente (Nice-Tree Decomposition) avec une largeur arborescente (treewidth) d’unité. Cette stratégie profite de la spécificité des DODAG et a abouti à une réduction significative de la complexité de la résolution du VCP sur les DODAG. Elle peut être résolue en temps polynomial.La deuxième proposition est un modèle approché pour l’optimisation de l’ordonnancement du rôle de monitorage des nœuds dans les réseaux IdO, afin de maximiser la durée de vie des dispositifs embarqués à ressources limitées, tout en minimisant le coût global du monitorage de réseau. Le monitorage de réseau est très coûteux, en particulier pour les réseaux à ressources limitées tels que l’IdO. Par conséquent, le monitorage doit être économe en énergie et avec des frais généraux minimaux sur la performance normale du réseau. Notre travail correspondant contient une proposition d’un modèle mathématique en trois phases pour assurer l’exigence d’une couverture des moniteurs tout en minimisant la consommation d’énergie de monitorage et les frais de communication.Notre modèle proposé décompose le problème abordé en trois problèmes d’optimisation bien connus, il s’agit du problème de couverture de sommets, problème d’affectation généralisé multi-objectives et problème de voyageur de commerce.Dans cette troisième partie, une approche exacte est proposée pour résoudre le problème décrit dans (Contribution 2). Comme nous avons vu, la décomposition en trois phases ne donne pas la solution exacte. Nous avons donc proposé une formulation exacte du problème qui consiste en un problème de l'affectation minimum des tâches de surveillance avec un fonctionnement de surveillance cyclique. Pour cela, nous avons formulé un programme en nombres entiers binaires. L'ordonnancement optimal garantit la couverture du graphe pour la surveillance avec une consommation d'énergie minimale
By connecting billions of things to the Internet, IoT created a plethora of applications that touch every aspect of human life. Time-sensitive, mission-critical services, require robust connectivity and strict reliability constraints. On the other hand, the IoT relies mainly on Low-power Lossy Networks, which are unreliable by nature due to their limited resources, hard duty cycles, dynamic topologies, and uncertain radio connectivity. Faults in LLNs are common rather than rare events, therefore, maintaining continuous availability of devices and reliability of communication, are critical factors to guarantee a constant, reliable flow of application data.After a comprehensive literature review, and up to our knowledge, it is clear that there is a call for a new approach to monitoring the unreliable nodes and links in an optimized, energy-efficient, proactive manner, and complete interoperability with IoT protocols. To target this research gap, our contributions address the correct assignment (placement) of the monitoring nodes. This problem is known as the minimum assignment problem, which is NP-hard. We target scalable monitoring by mapping the assignment problem into the well-studied MVC problem, also NP-hard. We proposed an algorithm to convert the DODAG into a nice-tree decomposition with its parameter (treewidth) restricted to the value one. As a result of these propositions, the monitor placement becomes only Fixed-Parameter Tractable, and can also be polynomial-time solvable.To prolong network longevity, the monitoring role should be distributed and balanced between the entire set of nodes. To that end, assuming periodical functioning, we propose in a second contribution to schedule between several subsets of nodes; each is covering the entire network. A three-phase centralized computation of the scheduling was proposed. The proposition decomposes the monitoring problem and maps it into three well-known sub-problems, for which approximation algorithms already exist in the literature. Thus, the computational complexity can be reduced.However, the one major limitation of the proposed three-phase decomposition is that it is not an exact solution. We provide the exact solution to the minimum monitor assignment problem with a duty-cycled monitoring approach, by formulating a Binary Integer Program (BIP). Experimentation is designed using network instances of different topologies and sizes. Results demonstrate the effectiveness of the proposed model in realizing full monitoring coverage with minimum energy consumption and communication overhead while balancing the monitoring role between nodes.The final contribution targeted the dynamic distributed monitoring placement and scheduling. The dynamic feature of the model ensures real-time adaptation of the monitoring schedule to the frequent instabilities of networks, and the distributed feature aims at reducing the communication overhead

With recent advances in electronics and communication technologies, our daily lives are immersed in an environment of Internet-connected smart things. Despite the great convenience brought by the development of these technologies, privacy concerns and security issues are two topics that deserve more attention. On one hand, as smart things continue to grow in their abilities to sense the physical world and capabilities to send information out through the Internet, they have the potential to be used for surveillance of any individuals secretly. Nevertheless, people tend to adopt wearable devices without fully understanding what private information can be inferred and leaked through sensor data. On the other hand, security issues become even more serious and lethal with the world embracing the Internet of Things (IoT). Failures in computing systems are common, however, a failure now in IoT may harm people's lives. As demonstrated in both academic research and industrial practice, a software vulnerability hidden in a smart vehicle may lead to a remote attack that subverts a driver's control of the vehicle. Our approach to the aforementioned challenges starts by understanding privacy leakage in the IoT era and follows with adding defense layers to the IoT system with attackers gaining increasing capabilities. The first question we ask ourselves is "what new privacy concerns do IoT bring". We focus on discovering information leakage beyond people's common sense from even seemingly benign signals. We explore how much private information we can extract by designing information extraction systems. Through our research, we argue for stricter access control on newly coming sensors. After noticing the importance of data collected by IoT, we trace where sensitive data goes. In the IoT era, edge nodes are used to process sensitive data. However, a capable attacker may compromise edge nodes. Our second research focuses on applying trusted hardware to build trust in large-scale networks under this circumstance. The application of trusted hardware protects sensitive data from compromised edge nodes. Nonetheless, if an attacker becomes more powerful and embeds malicious logic into code for trusted hardware during the development phase, he still can secretly steal private data. In our third research, we design a static analyzer for detecting malicious logic hidden inside code for trusted hardware. Other than the privacy concern of data collected, another important aspect of IoT is that it affects the physical world. Our last piece of research work enables a user to verify the continuous execution state of an unmanned vehicle. This way, people can trust the integrity of the past and present state of the unmanned vehicle.
Doctor of Philosophy
The past few years have witnessed a rising in computing and networking technologies. Such advances enable the new paradigm, IoT, which brings great convenience to people's life. Large technology companies like Google, Apple, Amazon are creating smart devices such as smartwatch, smart home, drones, etc. Compared to the traditional internet, IoT can provide services beyond digital information by interacting with the physical world by its sensors and actuators. While the deployment of IoT brings value in various aspects of our society, the lucrative reward from cyber-crimes also increases in the upcoming IoT era. Two unique privacy and security concerns are emerging for IoT. On one hand, IoT brings a large volume of new sensors that are deployed ubiquitously and collect data 24/7. User's privacy is a big concern in this circumstance because collected sensor data may be used to infer a user's private activities. On the other hand, cyber-attacks now harm not only cyberspace but also the physical world. A failure in IoT devices could result in loss of human life. For example, a remotely hacked vehicle could shut down its engine on the highway regardless of the driver's operation. Our approach to emerging privacy and security concerns consists of two directions. The first direction targets at privacy protection. We first look at the privacy impact of upcoming ubiquitous sensing and argue for stricter access control on smart devices. Then, we follow the data flow of private data and propose solutions to protect private data from the networking and cloud computing infrastructure. The other direction aims at protecting the physical world. We propose an innovative method to verify the cyber state of IoT devices.

O aumento na quantidade e na intensidade de desastres naturais é um problema que está se agravando em todo o mundo. As consequências desses desastres são significantemente ampliadas quando ocorrem em regiões urbanas ou com atuação humana devido à perda de vidas e à quantidade de bens materiais afetados. O uso de redes de sensores sem fio para a coleta de dados e o uso de técnicas de aprendizado de máquina para a previsão de desastres naturais são opções viáveis, porém novas tendências tecnológicas têm se mostrado promissoras e podem agregar na tarefa de monitoramento de ambientes e na previsão de desastres naturais. Uma dessas tendências é adotar redes de sensores baseadas em IP e utilizar padrões emergentes para IoT. Nesse contexto, esta Tese propõe e analisa uma abordagem chamada SENDI (System for dEtecting and forecasting Natural Disasters based on IoT), um sistema tolerante a falhas baseado em IoT, WSN e AM para a detecção e a previsão de desastres naturais. O SENDI foi modelado empregando o ns-3 e validado utilizando dados coletados por uma WSN real instalada na cidade de São Carlos - Brasil, a qual realiza a coleta de dados de rios da região. Esse sistema também prevê a possibilidade de falhas na comunicação e a perda de nós durante a ocorrência de desastres, além de agregar inteligência aos nós para realizar a distribuição de dados e de previsões, mesmo nesses casos. Esta Tese também apresenta um estudo de caso sobre previsão de enchentes que utiliza a modelagem do sistema e os dados colhidos pela WSN. Os resultados dos experimentos mostram que o SENDI permite gerar alertas para a tomada de decisões em tempo hábil, realizando as previsões mesmo com falhas parciais no sistema, porém com acurácia variável dependendo do nível de degradação do mesmo.
Natural disasters have been increasing intensely all around the globe. The consequences of these disasters are significantly amplified when they occur in urban areas or places where there are human activities due to loss of lives and assets. The usage of Wireless Sensor Networks (WSN) for data collection and Machine Learning (ML) to create natural disasters forecast models are viable options. However, new technology trends have been showing promising results, which can aggregate to the tasks of environmental monitoring and natural disasters forecast. One of these new trends is to adopt IP based sensor networks and to use emergent Internet of Things (IoT) standards. In this context, this Thesis presents and analyzes an approach called SENDI (System for dEtecting and forecasting Natural Disasters based on IoT), a fault-tolerant system based on IoT, ML and WSN to detect and forecast natural disasters. SENDI was modelled using ns-3 and validated by means of real data collected by a WSN installed in São Carlos - Brazil, which collects the data of rivers around the region. This system also foresees the possibility of communication failures and loss of nodes during disasters, also adding intelligence to the nodes in order to perform the distribution of data and forecasts, even in such cases. This Thesis presents a case study about flash flooding forecast as well, which uses the system model and the data collected by the WSN. The results of the experiments show that SENDI allows to generate warnings in time to make decisions as such predictions can be foreseen even if partial failure of the system occurs. However, there is a variable accuracy, which depends on the system degradation.

The Diploma work deals with the implementation of LTE Cat-M technology in the simulation tool Network Simulator 3 (NS-3). The work describe LPWA technologies and their use cases. In first are described the main parts of the Internet of Things (IoT) and Machine-to-Machine (M2M) communication. Subsequently are described and defined the most used technologies in LPWA networks. Technologies which are used in the LPWA networks are Sigfox, LoRaWAN, Narrowband IoT (NB-IoT) and Long Term Evolution for Machines (LTE Cat-M), where LTE Cat-M technology is described in more details. Simulations are simulated in simulation tool NS-3 and use LENA module. In NS 3 tool are simulated Simulations, which give us informations of Network state according to different Network set up. At the end are done changes of Radio Resource Control (RRC) states in NS-3 tool. These changes are required for correct implementation LTE Cat-M technology in NS-3 tool. Then we are able to simulate simulations, which meet to definition of LTE Cat-M technology.

Made available in DSpace on 2019-03-30T00:02:10Z (GMT). No. of bitstreams: 0 Previous issue date: 2018-11-26
Recent advances in networking technologies, such as the IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN) standard, have allowed to interconnect wireless sensor networks (WSNs) to the Internet, thus forming the Internet of Things (IoT). Despite the availability of different message security mechanisms, sensor networks are still vulnerable to several types of attack. To identify such attacks, an Intrusion Detection System (IDS) can be deployed. However, IDSs can generate several false positives and false negatives. Moreover, the alerts raised by IDSs provide no information regarding the impact an attack has on the security of a sensor network. As a consequence, it becomes difficult for WSN administrators and users to take proper responsive actions when attacks occur. To address these issues, this thesis proposes three security metrics. The first metric, called Trust Probability, quantifies by how much an IDS output could be trusted (to be correct). Such metric can help administrators decide which alerts deserve careful attention or which alerts might be safely ignored. Since this type of metric provides a measure of IDS effectiveness, it can also be used to compare different IDSs as well as to fine-tune a given IDS. The second metric, named Damage Level, quantifies the severity of an attack. This metric, when combined with the Trust Probability metric, enables the administrator to correctly prioritize and respond to alerts by evaluating them in terms of accuracy and attack impact. Finally, the third metric, namely Data Security Level, quantifies the degree to which sensor data can be trusted when the sensor is under attack. The security situational awareness provided by this metric helps WSN users make better decisions about the use of the gathered sensor data. Experimental results show that the proposed metrics can accurately quantify security level with low performance overhead and power consumption. Keywords: Network Security Metrics, Quantitative Security Analysis, Security Situational Awareness, Internet of Things, Wireless Sensor Networks.
Recentes avanços nas tecnologias de rede, tais como o padrão IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN), permitiram a interconexão de redes de sensores sem fio (RSSF) à Internet, formando assim a Internet das Coisas (Internet of Things -- IoT). Apesar da disponibilidade de diferentes mecanismos de segurança de mensagens, as redes de sensores ainda são vulneráveis a vários tipos de ataques. Para identificar esses ataques, um Sistema de Detecção de Intrusão (Intrusion Detection System -- IDS) pode ser implantado. No entanto, os IDSs podem gerar vários falsos positivos e falsos negativos. Além disso, os alertas gerados pelos IDSs não fornecem nenhuma informação sobre o impacto de um ataque sobre a segurança de uma RSSF. Consequentemente, torna-se difícil para os administradores e usuários da rede tomarem as devidas ações responsivas quando ataques ocorrerem. Para tratar estas questões, esta tese propõe três métricas de segurança. A primeira delas, chamada Trust Probability, quantifica o quão confiável (correto) é um output de um IDS. Essa métrica pode ajudar os administradores a decidir quais alertas merecem mais atenção ou quais podem ser ignorados com segurança. Já que essa métrica fornece uma medida da efetividade de um IDS, ela também pode ser usada para comparar diferentes IDSs, bem como para otimizar um dado IDS. A segunda métrica, denominada Damage Level, quantifica a gravidade de um ataque. Esta métrica, quando combinada com a Trust Probability, permite ao administrador priorizar e responder corretamente a alertas, avaliando-os em termos de precisão e impacto de ataque. Por fim, a terceira métrica, chamada de Data Security Level, quantifica quão confiáveis os dados dos sensores são quando a rede está sob ataque. Conhecer a informação fornecida por esta métrica ajuda os usuários a tomar melhores decisões sobre o uso dos dados coletados pelos sensores. Os resultados experimentais mostram que as métricas propostas podem quantificar com precisão o nível de segurança da rede, com baixo consumo de energia e sobrecarga de desempenho. Palavras-chave:Métricas de Segurança de Rede, Análise Quantitativa de Segurança, Consciência Situacional de Segurança, Internet das Coisas, Redes de Sensores sem Fio.

Technology Narrowband IoT is a representative LPWA (Low Power Wide Area) tech-nology that due to its promising features aims for demands of the Internet of Thingsapplications for autonomous data sending from sensors in areas of poor mobile coverage.For such applications, it is beneficial to firstly map properties of communication technol-ogy in areas of intended use and evaluate whether or not is this technology applicable.This Master thesis deals with the design of the hand-held measuring device for evaluationof Narrowband IoT properties. The output of this thesis is firstly comparison of LPWAtechnologies secondly, design of the mentioned device and verification of its functional-ity. And in last part description of measurement of transmission delay for delay-tolerantapplications. Transmission delay is a critical parameter for delay-tolerant applications.Such an application can be, for example, smart electrometers for which there is definedmaximal allowed transmission delay of 10 seconds and therefore it is desirable to evalu-ate whether or not is the deployment of the communication technology Narrowband IoTsuitable in the intended area for delay-tolerant or even for delay-intolerant applications.

Cognitive Radio Internet of Things (CR-IoT) has revolutionized almost every field of life and reshaped the technological world. Several tiny devices are seamlessly connected in a CR-IoT network to perform various tasks in many applications. Nevertheless, CR-IoT surfers from malicious attacks that pulverize communication and perturb network performance. Therefore, recently it is envisaged to introduce higher-level Artificial Intelligence (AI) by incorporating Self-Awareness (SA) capabilities into CR-IoT objects to facilitate CR-IoT networks to establish secure transmission against vicious attacks autonomously. In this context, sub-band information from the Orthogonal Frequency Division Multiplexing (OFDM) modulated transmission in the spectrum has been extracted from the radio device receiver terminal, and a generalized state vector (GS) is formed containing low dimension in-phase and quadrature components. Accordingly, a probabilistic method based on learning a switching Dynamic Bayesian Network (DBN) from OFDM transmission with no abnormalities has been proposed to statistically model signal behaviors inside the CR-IoT spectrum. A Bayesian filter, Markov Jump Particle Filter (MJPF), is implemented to perform state estimation and capture malicious attacks. Subsequently, GS containing a higher number of subcarriers has been investigated. In this connection, Variational autoencoders (VAE) is used as a deep learning technique to extract features from high dimension radio signals into low dimension latent space z, and DBN is learned based on GS containing latent space data. Afterward, to perform state estimation and capture abnormalities in a spectrum, Adapted-Markov Jump Particle Filter (A-MJPF) is deployed. The proposed method can capture anomaly that appears due to either jammer attacks in transmission or cognitive devices in a network experiencing different transmission sources that have not been observed previously. The performance is assessed using the receiver operating characteristic (ROC) curves and the area under the curve (AUC) metrics.

Робота містить 70 сторінок, 15 рисунків, та 10 таблиць. Було використано 35 джерел. Мета роботи: підвищити енергоефективність сенсорної мережі IoT за рахунок модифікації методу передачі інформації, що дозволить збільшити час роботи вузлів збору та передачі інформації сенсорної мережі IoT. Проведено детальний аналіз проблем Інтернету речей, особливу увагу було звернено на питання модернізації архітектури мережі задля підвищення енергоефективності та збільшення терміну служби мережі. Детально розібрано метод випадкового циклу Sleep/Wake. Поставлено та виконано завдання модифікації архітектури бездротової сенсорної мережі Інтернету речей. Запропоновано координований метод циклу Sleep/Wake для передачі пакетів інформації в межах сенсорної мережі Інтернету речей. Після проведення оцінки нового методу та його імітаційного моделювання, було зроблено висновок, що такий модифікований метод може бути корисним для впровадження, оскільки: 1. Життєвий цикл мережі за допомогою запропонованого координованого методу обчислення робочого циклу та визначення черг збільшився від 3,8% до 11,25%. 2. Збільшився термін служби сенсорної мережі в порівнянні з асинхронним циклом черг в сенсорних мережах Інтернету речей від 8,4% до 14,8%.
The thesis contains 70 pages, 15 figures, and 10 tables. 35 sources have been used. The purpose of the work is to increase the energy efficiency of the IoT sensor network by modifying the method of information transmission, which will increase the operating time of the nodes of collection and transmission of information of the IoT sensor network. The detailed analysis of the problems of the Internet of Things has been made. Special attention has been paid to modernizing the architecture of the network for improving its energy efficiency and extending its lifetime. The method of random Sleep/Wake cycle has been analyzed in detail. The task to modify the architecture of the wireless sensorу network of the Internet of Things has been fulfilled. The co-ordinated Sleep/Wake cycle method is proposed for transmitting information packets within the sensory network of the Internet of Things. After evaluating the new method and its simulation model, it was concluded that this modified method might be useful for implementation, since: 1. The life cycle of the network with the proposed coordinated method for calculating the duty cycle and queue determination increased from 3.8% to 11.25%. 2. The lifetime of the sensory network increased from 8.4% to 14.8%, compared to the asynchronous cycle of queues in the sensory networks of the Internet of Things.

Зпроектовано інтелектуальну мережу «розумного будинку» у симуляторі Cisco Packet Tracer_7, яка базується на роботі дротової та бездротової мереж, де усі пристрої звязані зі шлюзом. Доступ контролю та моніторингу забезпечено з планшету та смартфону через зручний веб-інтерфейс. Для налаштування пожежної безпеки було розроблено програму для мікроконтролера на мові JavaScript. Візуальне програмування було використано для забезпечення системи комфорту. Розроблена схема при тестуванні показала високі результати, що говорить про доступність та зрозумілість взаємодії із можливостями симулятора. Вона дає змогу отримати наочне уявлення про функціонування розгалудженої системи «розумного будинку» та навчитися формулювати правила роботи окремих елементів на базі отриманих показників датчиків і сенсорів.

La quinta generación de redes móviles (5G) se encuentra a la vuelta de la esquina. Se espera provea de beneficios extraordinarios a la población y que resuelva la mayoría de los problemas de las redes 4G actuales. El éxito de 5G, cuya primera fase de estandarización ha sido completada, depende de tres pilares: comunicaciones tipo-máquina masivas, banda ancha móvil mejorada y comunicaciones ultra fiables y de baja latencia (mMTC, eMBB y URLLC, respectivamente). En esta tesis nos enfocamos en el primer pilar de 5G, mMTC, pero también proveemos una solución para lograr eMBB en escenarios de distribución masiva de contenidos. Específicamente, las principales contribuciones son en las áreas de: 1) soporte eficiente de mMTC en redes celulares; 2) acceso aleatorio para el reporte de eventos en redes inalámbricas de sensores (WSNs); y 3) cooperación para la distribución masiva de contenidos en redes celulares. En el apartado de mMTC en redes celulares, esta tesis provee un análisis profundo del desempeño del procedimiento de acceso aleatorio, que es la forma mediante la cual los dispositivos móviles acceden a la red. Estos análisis fueron inicialmente llevados a cabo por simulaciones y, posteriormente, por medio de un modelo analítico. Ambos modelos fueron desarrollados específicamente para este propósito e incluyen uno de los esquemas de control de acceso más prometedores: access class barring (ACB). Nuestro modelo es uno de los más precisos que se pueden encontrar en la literatura y el único que incorpora el esquema de ACB. Los resultados obtenidos por medio de este modelo y por simulación son claros: los accesos altamente sincronizados que ocurren en aplicaciones de mMTC pueden causar congestión severa en el canal de acceso. Por otro lado, también son claros en que esta congestión se puede prevenir con una adecuada configuración del ACB. Sin embargo, los parámetros de configuración del ACB deben ser continuamente adaptados a la intensidad de accesos para poder obtener un desempeño óptimo. En la tesis se propone una solución práctica a este problema en la forma de un esquema de configuración automática para el ACB; lo llamamos ACBC. Los resultados muestran que nuestro esquema puede lograr un desempeño muy cercano al óptimo sin importar la intensidad de los accesos. Asimismo, puede ser directamente implementado en redes celulares para soportar el tráfico mMTC, ya que ha sido diseñado teniendo en cuenta los estándares del 3GPP. Además de los análisis descritos anteriormente para redes celulares, se realiza un análisis general para aplicaciones de contadores inteligentes. Es decir, estudiamos un escenario de mMTC desde la perspectiva de las WSNs. Específicamente, desarrollamos un modelo híbrido para el análisis de desempeño y la optimización de protocolos de WSNs de acceso aleatorio y basados en cluster. Los resultados muestran la utilidad de escuchar el medio inalámbrico para minimizar el número de transmisiones y también de modificar las probabilidades de transmisión después de una colisión. En lo que respecta a eMBB, nos enfocamos en un escenario de distribución masiva de contenidos, en el que un mismo contenido es enviado de forma simultánea a un gran número de usuarios móviles. Este escenario es problemático, ya que las estaciones base de la red celular no cuentan con mecanismos eficientes de multicast o broadcast. Por lo tanto, la solución que se adopta comúnmente es la de replicar e contenido para cada uno de los usuarios que lo soliciten; está claro que esto es altamente ineficiente. Para resolver este problema, proponemos el uso de esquemas de network coding y de arquitecturas cooperativas llamadas nubes móviles. En concreto, desarrollamos un protocolo para la distribución masiva de contenidos, junto con un modelo analítico para su optimización. Los resultados demuestran que el modelo propuesto es simple y preciso, y que el protocolo puede reducir el con
La cinquena generació de xarxes mòbils (5G) es troba molt a la vora. S'espera que proveïsca de beneficis extraordinaris a la població i que resolga la majoria dels problemes de les xarxes 4G actuals. L'èxit de 5G, per a la qual ja ha sigut completada la primera fase del qual d'estandardització, depén de tres pilars: comunicacions tipus-màquina massives, banda ampla mòbil millorada, i comunicacions ultra fiables i de baixa latència (mMTC, eMBB i URLLC, respectivament, per les seues sigles en anglés). En aquesta tesi ens enfoquem en el primer pilar de 5G, mMTC, però també proveïm una solució per a aconseguir eMBB en escenaris de distribució massiva de continguts. Específicament, les principals contribucions són en les àrees de: 1) suport eficient de mMTC en xarxes cel·lulars; 2) accés aleatori per al report d'esdeveniments en xarxes sense fils de sensors (WSNs); i 3) cooperació per a la distribució massiva de continguts en xarxes cel·lulars. En l'apartat de mMTC en xarxes cel·lulars, aquesta tesi realitza una anàlisi profunda de l'acompliment del procediment d'accés aleatori, que és la forma mitjançant la qual els dispositius mòbils accedeixen a la xarxa. Aquestes anàlisis van ser inicialment dutes per mitjà de simulacions i, posteriorment, per mitjà d'un model analític. Els models van ser desenvolupats específicament per a aquest propòsit i inclouen un dels esquemes de control d'accés més prometedors: el access class barring (ACB). El nostre model és un dels més precisos que es poden trobar i l'únic que incorpora l'esquema d'ACB. Els resultats obtinguts per mitjà d'aquest model i per simulació són clars: els accessos altament sincronitzats que ocorren en aplicacions de mMTC poden causar congestió severa en el canal d'accés. D'altra banda, també són clars en què aquesta congestió es pot previndre amb una adequada configuració de l'ACB. No obstant això, els paràmetres de configuració de l'ACB han de ser contínuament adaptats a la intensitat d'accessos per a poder obtindre unes prestacions òptimes. En la tesi es proposa una solució pràctica a aquest problema en la forma d'un esquema de configuració automàtica per a l'ACB; l'anomenem ACBC. Els resultats mostren que el nostre esquema pot aconseguir un acompliment molt proper a l'òptim sense importar la intensitat dels accessos. Així mateix, pot ser directament implementat en xarxes cel·lulars per a suportar el trànsit mMTC, ja que ha sigut dissenyat tenint en compte els estàndards del 3GPP. A més de les anàlisis descrites anteriorment per a xarxes cel·lulars, es realitza una anàlisi general per a aplicacions de comptadors intel·ligents. És a dir, estudiem un escenari de mMTC des de la perspectiva de les WSNs. Específicament, desenvolupem un model híbrid per a l'anàlisi de prestacions i l'optimització de protocols de WSNs d'accés aleatori i basats en clúster. Els resultats mostren la utilitat d'escoltar el mitjà sense fil per a minimitzar el nombre de transmissions i també de modificar les probabilitats de transmissió després d'una col·lisió. Pel que fa a eMBB, ens enfoquem en un escenari de distribució massiva de continguts, en el qual un mateix contingut és enviat de forma simultània a un gran nombre d'usuaris mòbils. Aquest escenari és problemàtic, ja que les estacions base de la xarxa cel·lular no compten amb mecanismes eficients de multicast o broadcast. Per tant, la solució que s'adopta comunament és la de replicar el contingut per a cadascun dels usuaris que ho sol·liciten; és clar que això és altament ineficient. Per a resoldre aquest problema, proposem l'ús d'esquemes de network coding i d'arquitectures cooperatives anomenades núvols mòbils. En concret, desenvolupem un protocol per a realitzar la distribució massiva de continguts de forma eficient, juntament amb un model analític per a la seua optimització. Els resultats demostren que el model proposat és simple i precís
The 5th generation (5G) of mobile networks is just around the corner. It is expected to bring extraordinary benefits to the population and to solve the majority of the problems of current 4th generation (4G) systems. The success of 5G, whose first phase of standardization has concluded, relies in three pillars that correspond to its main use cases: massive machine-type communication (mMTC), enhanced mobile broadband (eMBB), and ultra-reliable low latency communication (URLLC). This thesis mainly focuses on the first pillar of 5G: mMTC, but also provides a solution for the eMBB in massive content delivery scenarios. Specifically, its main contributions are in the areas of: 1) efficient support of mMTC in cellular networks; 2) random access (RA) event-reporting in wireless sensor networks (WSNs); and 3) cooperative massive content delivery in cellular networks. Regarding mMTC in cellular networks, this thesis provides a thorough performance analysis of the RA procedure (RAP), used by the mobile devices to switch from idle to connected mode. These analyses were first conducted by simulation and then by an analytical model; both of these were developed with this specific purpose and include one of the most promising access control schemes: the access class barring (ACB). To the best of our knowledge, this is one of the most accurate analytical models reported in the literature and the only one that incorporates the ACB scheme. Our results clearly show that the highly-synchronized accesses that occur in mMTC applications can lead to severe congestion. On the other hand, it is also clear that congestion can be prevented with an adequate configuration of the ACB scheme. However, the configuration parameters of the ACB scheme must be continuously adapted to the intensity of access attempts if an optimal performance is to be obtained. We developed a practical solution to this problem in the form of a scheme to automatically configure the ACB; we call it access class barring configuration (ACBC) scheme. The results show that our ACBC scheme leads to a near-optimal performance regardless of the intensity of access attempts. Furthermore, it can be directly implemented in 3rd Generation Partnership Project (3GPP) cellular systems to efficiently handle mMTC because it has been designed to comply with the 3GPP standards. In addition to the analyses described above for cellular networks, a general analysis for smart metering applications is performed. That is, we study an mMTC scenario from the perspective of event detection and reporting WSNs. Specifically, we provide a hybrid model for the performance analysis and optimization of cluster-based RA WSN protocols. Results showcase the utility of overhearing to minimize the number of packet transmissions, but also of the adaptation of transmission parameters after a collision occurs. Building on this, we are able to provide some guidelines that can drastically increase the performance of a wide range of RA protocols and systems in event reporting applications. Regarding eMBB, we focus on a massive content delivery scenario in which the exact same content is transmitted to a large number of mobile users simultaneously. Such a scenario may arise, for example, with video streaming services that offer a particularly popular content. This is a problematic scenario because cellular base stations have no efficient multicast or broadcast mechanisms. Hence, the traditional solution is to replicate the content for each requesting user, which is highly inefficient. To solve this problem, we propose the use of network coding (NC) schemes in combination with cooperative architectures named mobile clouds (MCs). Specifically, we develop a protocol for efficient massive content delivery, along with the analytical model for its optimization. Results show the proposed model is simple and accurate, and the protocol can lead to energy savings of up to 37 percent when compared to the traditional approach.
Leyva Mayorga, I. (2018). On reliable and energy efficient massive wireless communications: the road to 5G [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/115484
TESIS

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The objective of this work is to monitor the electrical equipment of a production line, aiming at monitoring in real time the state of the operation of the monitored machines, allowing the accomplishment of equipment management and early detection of operational deviations and faults. The developed system performs the measurement of the effective electric current through monitored equipment, use a network of sensors connected to a data concentrator module, which in turn performs the intermediate storage, the preliminary treatment of the data and the subsequent send an Internet platform of Things (Internet of Things - IoT). The preliminary treatment of data for analysis of the time series of values of electric currents to obtain an initial evaluation of the state of operation of the monitored machine. Then, the pre-processed information is sent via the internet, a usage platform for term storage, post-processing and real-time visualization of the data by users of interest. In the data platform, the data is formatted for visualization and evaluation of the users, allowing the presentation of alerts and knowledge when deviations are detected in relation to the normal operational parameters. When a current consumption behavior deviation is detected, correlating a potential failure type, the system signals additional information to a User's interest group (to the supervisor of the production line, for example), which in a planned manner, proceeds to some intervention without equipment, without prejudice of the production. The availability of the full-time series of stored data as well as the history of occurrences recorded throughout the use of the monitoring system but is still looking for correlations between data of other origins and nature, and the interpretation of the same data under other perspectives beyond the operation or maintenance of the machine. The monitoring system proposed in this work allows to provide a minimum of automation in old machines and opens the possibility of independent, parallel and non-intrusive monitoring in machines that already have a modern supervisory system. An industry that achieves the goal of making all its production equipment fully monitored is credited to take the next step towards Industry 4.0.
Este trabalho tem como objetivo apresentar um sistema de monitoramento de equipamentos el?tricos de uma linha de produ??o, visando o acompanhamento em tempo real do estado de opera??o das m?quinas monitoradas, permitindo a realiza??o da gest?o de opera??o desses equipamentos e a detec??o antecipada de desvios operacionais e de falhas. O sistema desenvolvido realiza a medi??o da corrente el?trica eficaz consumida pelos equipamentos monitorados, utilizando uma rede de sensores conectados a um m?dulo concentrador de dados, que por sua vez realiza o armazenamento intermedi?rio, o tratamento preliminar dos dados e o posterior envio a uma plataforma de Internet da Coisas (Internet of Things - IoT). O tratamento preliminar de dados visa ? an?lise da s?rie temporal dos valores das correntes el?tricas com o fim de obter uma avalia??o inicial do estado de opera??o da m?quina monitorada. Em seguida, essas informa??es pr?-processadas s?o enviadas via internet a uma plataforma de IoT com o objetivo de armazenamento a longo prazo, p?s-processamento e visualiza??o em tempo real dos dados pelos usu?rios de interesse. Na plataforma de IoT, os dados s?o formatados para exibi??o e avalia??o dos usu?rios considerando formatos gr?ficos compreens?veis, sendo poss?vel a emiss?o de alertas e de relat?rios ao serem detectados desvios em rela??o aos par?metros operacionais normais. Ao ser detectado um desvio de comportamento no consumo de corrente, correlacionando a algum tipo de falha em potencial, o sistema sinaliza informa??es adicionais a um usu?rio de interesse (ao supervisor da linha de produ??o, por exemplo), que de forma planejada, procede a alguma interven??o no equipamento, sem preju?zo da produ??o. A disponibilidade da s?rie temporal completa dos dados armazenados bem como o hist?rico de ocorr?ncias registrados ao longo do uso do sistema de monitoramento permite ainda a busca de correla??es entre dados de outras origens e naturezas, e a interpreta??o dos mesmos dados sob outras ?ticas em contextos al?m da opera??o ou manuten??o da m?quina. O sistema de monitoramento proposto permite prover um m?nimo de automa??o em m?quinas antigas e abre a possibilidade de monitoramento independente, paralela e n?o intrusiva em m?quinas que j? contam com um sistema supervis?rio moderno. Uma ind?stria que atinja o objetivo de tornar o conjunto de seus equipamentos produtivos totalmente monitorado se credencia para dar o pr?ximo passo rumo ? Ind?stria 4.0.

According to World Health Organization, around 7 million people die every year due to diseases caused by air pollution. With the improvements in Internet of Things in the recent years, environmental sensing systems has started to gain importance. By using technologies like Cloud Computing, RFID, Wireless Sensor Networks, and open Application Programming Interfaces, it has become easier to collect data for visualization on different platforms. However, collected data need to be represented in an efficient way for better understanding and analysis, which requires design of data visualization tools. The GreenIoT initiative aims to provide open data with its infrastructure for sustainable city development in Uppsala. An environmental web application is presented within this thesis project, which visualizes the gathered environmental data to help municipality organizations to implement new policies for sustainable urban planning, and citizens to gain more knowledge to take sustainable decisions in their daily life. The application has been developed making use of the 4Dialog API, which is developed to provide data from a dedicated cloud storage for visualization purposes. According to the evaluation presented in this thesis, further development is needed to improve the performance to provide faster and more reliable service as well as the accessibility to promote openness and social inclusion.
Enligt World Health Organization dör 7 miljoner människor varje år på grund av sjukdomar orsakade av luftföroreningar. Med förbättringar inom Internet of Things under senare år, har betydelsen av system för miljösensorer. Genom att använda tekniker som molntjänster, RFID, trådlösa sensornätverk och öppna programmeringsgränssnitt, har det blivit enklare att samla in data för visualisering på olika plattformar. Men insamlad data behöver bli representerad på ett effektivt sätt för bättre förståelse och analys, vilket kräver utformande av verktyg för visualisering av data. Initiativet GreenIoT strävar mot att erbjuda öppen data med sin infrastruktur för hållbar stadsutveckling i Uppsala. I detta arbete presenteras en webb-tillämpning, som visualiserar den insamlade miljödatan för att hjälpa kommunen att implementera nya policies för hållbar stadsutveckling, och stimulera medborgare till att skaffa mer kunskap för att göra miljövänliga val i sin vardag. Tillämpningen har utvecklats med hjälp av 4Dialog API, som tillhandahåller data från lagring i molnet för visualiseringssyfte. Enligt den utvärdering som presenteras i denna rapport konstateras att vidare utveckling behövs för att förbättra dels prestanda för att erbjuda en snabbare och mer tillförlitlig service, och dels åtkomstmöjligheter för att främja öppenhet och social inkludering.

La mobilité devienne un partie intégrante de l’Internet des Object d’aujourd’hui, comme beaucoup d’applications (monitorage des animaux sauvage, suivi des cible dans le champs de bataille) sont impossible de mettre en œuvre juste avec des nœuds statiques. L’objective de cette thèse est de définir une nouvelle architecture de communication articule autour de la mobilité dans les réseaux avec pertes et à bas puissance (Low Power and Lossy Networks - LLNs) (réseaux des capteurs sans fils). Tout d’abord, nous avons analysé théoriquement l’auto configuration des adresses IPv6, fait avec toutes les optimisations disponibles dans Neighbor Discovery Optimization for IPv6 over 6LoWPAN. Cette étape est cruciale pour des protocoles qui donnent de support pour la mobilité dans des réseaux IP, comme MIPv6. Les résultats obtenues – taille des paquets trop grande et consumations énergétique importante pour les routeurs qui tournent Neighbor Discovery – n’ont amener a utiliser le IPv6 Routing Protocol for Low Power and Lossy Networks (RPL). RPL est développe d’el debout pour les LLN. Notre deuxième contribution sont améliorer les opérations du RPL pour mieux supporter les nœuds mobiles. Enfin, nous avons développe une mécanisme inter-couche – Mobility Triggered-RPL – qui profite des actions dans le protocole avec préambule X-Machiavel à la couche accès au medium dans le protocole RPL à la couche routage
Mobility is becoming an integrating part of todays Internet of Things, as many applications such as wildlife monitoring or target tracking in the battlefield cannot be done only with the help of static nodes. The goal of this thesis is to provide new communication architecture articulated around providing mobility support in Low Power and Lossy Networks (LLNs). First we analyzed from a theoretical point of view the IPv6 address auto-configuration with all optimizations made in Neighbor Discovery Optimization for IPv6 over 6LoWPAN. This step is of crucial importance for protocols that offer mobility support in IP networks, such as MIPv6. Our findings, increased message size that leads to fragmentation and high energy consumption for routers that are involved in Neighbor Discovery message exchange, have lead us to use the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL) in order to provide mobility support. RPL is build from ground up with respect to LLN requirements. Our second contribution enhanced RPL operations to support mobility management. Finally, we proposed a cross-layer protocol – Mobility Triggered-RPL – that leverages actions from the X-Machiavel preamble sampling MAC protocol into RPL