Dans les prochaines années, l’Internet des objets (IoT) constituera l’une des applications générant le plus de données. Actuellement, les données de l’IoT sont stockées dans le Cloud. Avec l’augmentation du nombre d’objets connectés, la transmission de la grande quantité de données produite vers le Cloud génèrera des goulets d’étranglement. Par conséquent, les latences seront élevées. Afin de réduire ces latences, le Fog computing a été proposé comme un paradigme étendant les services du Cloud jusqu’aux périphéries du réseau. Il consiste à utiliser tout équipement localisé dans le réseau (ex. routeur) pour faire le stockage et le traitement des données. Cependant, le Fog présente une infrastructure hétérogène. En effet, ses équipements présentent des différences de performances de calcul, de capacités de stockage et d’interconnexions réseaux.Cette hétérogénéité peut davantage augmenter la latence du service. Cela pose un problème : le mauvais choix des emplacements de stockage des données peut augmenter la latence du service. Dans cette thèse, nous proposons une solution à ce problème sous la forme de quatre contributions : 1. Une formulation du problème de placement de données de l’IoT dans le Fog comme un programme linéaire. 2. Une solution exacte pour résoudre le problème de placement de données en utilisant CPLEX, un solveur de problème linéaire. 3. Deux heuristiques basées sur le principe de “diviser pour régner” afin de réduire le temps du calcul de placement. 4. Une plate-forme expérimentale pour évaluer des solutions de placement de données de l’IoT dans le Fog, en intégrant la gestion du placement de données à iFogSim, un simulateur d’environnement Fog et IoT. / In the coming years, Internet of Things (IoT) will be one of the applications generating the most data. Nowadays, IoT data is stored in the Cloud. As the number of connected objects increases, transmitting the large amount of produced data to the Cloud will create bottlenecks. As a result, latencies will be high and unpredictable. In order to reduce these latencies, Fog computing has been proposed as a paradigm extending Cloud services to the edge of the network. It consists of using any equipment located in the network (e.g. router) to store and process data. Therefore, the Fog presents a heterogeneous infrastructure. Indeed, its components have differences in computing performance, storage capacity and network interconnections. This heterogeneity can further increase the latency of the service. This raises a problem: the wrong choice of data storage locations can increase the latency of the service. In this thesis, we propose a solution to this problem in the form of four contributions: 1. A formulation of the IoT data placement problem in the Fog as a linear program. 2. An exact solution to solve the data placement problem using the CPLEX, a mixed linear problem solver. 3. Two heuristics based on the principle of “divide and conquer” to reduce the time of placement computation. 4. An experimental platform for testing and evaluating solutions for IoT data placement in the Fog, integrating data placement management with iFogSim, a Fog and IoT environment simulator.

L’Internet des Objets (IoT) vise à créer un eco-système global et ubiquitaire composé d’un grand nombre d’objets hétérogènes. Afin d’atteindre cette vision, le World Wide Web apparaît comme un candidat adapté pour interconnecter objets et services à la couche applicative en un Web des Objets (WoT).Cependant l’évolution actuelle du WoT produit des silos d’objets et empêche ainsi la mise en place de cette vision. De plus, même si le Web facilite la composition d’objets et services hétérogènes, les approches existantes produisent des compositions statiques incapables de s’adapter à des environnements dynamiques et des exigences évolutives. Un autre défi est à relever: permettre aux personnes d’interagir avec le vaste, évolutif et hétérogène IoT.Afin de répondre à ces limitations, nous proposons une architecture pour IoT ouvert et autogouverné, constitué de personnes et d’objets situés, en interaction avec un environnement global via des plateformes hétérogènes. Notre approche consiste de rendre les objets autonomes et d’appliquer la métaphore des réseaux sociaux afin de créer des réseaux flexibles de personnes et d’objets. Nous fondons notre approche sur les résultats issus des domaines des multi-agents et du WoT afin de produit un WoT Social.Notre proposition prend en compte les besoins d’hétérogénéité, de découverte et d’interaction flexible dans l’IoT. Elle offre également un coût minimal pour les développeurs et les utilisateurs via différentes couches d’abstraction permettant de limité la complexité de cet éco-système. Nous démontrons ces caractéristiques par la mise en oeuvre de plus scénarios applicatifs. / The Internet of Things (IoT) aims to create a global ubiquitous ecosystem composed of large numbers of heterogeneous devices. To achieve this vision, the World Wide Web is emerging as a suitable candidate to interconnect IoT devices and services at the application layer into a Web of Things (WoT).However, the WoT is evolving towards large silos of things, and thus the vision of a global ubiquitous ecosystem is not fully achieved. Furthermore, even if the WoT facilitates mashing up heterogeneous IoT devices and services, existing approaches result in static IoT mashups that cannot adapt to dynamic environments and evolving user requirements. The latter emphasizes another well-recognized challenge in the IoT, that is enabling people to interact with a vast, evolving, and heterogeneous IoT.To address the above limitations, we propose an architecture for an open and self-governed IoT ecosystem composed of people and things situated and interacting in a global environment sustained by heterogeneous platforms. Our approach is to endow things with autonomy and apply the social network metaphor to createflexible networks of people and autonomous things. We base our approach on results from multi-agent and WoT research, and we call the envisioned IoT ecosystem the Social Web of Things.Our proposal emphasizes heterogeneity, discoverability and flexible interaction in the IoT. In the same time, it provides a low entry-barrier for developers and users via multiple layers of abstraction that enable them to effectively cope with the complexity of the overall ecosystem. We implement several application scenarios to demonstrate these features.

L’Internet des Objets (IoT) vise à créer un eco-système global et ubiquitaire composé d’un grand nombre d’objets hétérogènes. Afin d’atteindre cette vision, le World Wide Web apparaît comme un candidat adapté pour interconnecter objets et services à la couche applicative en un Web des Objets (WoT).Cependant l’évolution actuelle du WoT produit des silos d’objets et empêche ainsi la mise en place de cette vision. De plus, même si le Web facilite la composition d’objets et services hétérogènes, les approches existantes produisent des compositions statiques incapables de s’adapter à des environnements dynamiques et des exigences évolutives. Un autre défi est à relever: permettre aux personnes d’interagir avec le vaste, évolutif et hétérogène IoT.Afin de répondre à ces limitations, nous proposons une architecture pour IoT ouvert et autogouverné, constitué de personnes et d’objets situés, en interaction avec un environnement global via des plateformes hétérogènes. Notre approche consiste de rendre les objets autonomes et d’appliquer la métaphore des réseaux sociaux afin de créer des réseaux flexibles de personnes et d’objets. Nous fondons notre approche sur les résultats issus des domaines des multi-agents et du WoT afin de produit un WoT Social.Notre proposition prend en compte les besoins d’hétérogénéité, de découverte et d’interaction flexible dans l’IoT. Elle offre également un coût minimal pour les développeurs et les utilisateurs via différentes couches d’abstraction permettant de limité la complexité de cet éco-système. Nous démontrons ces caractéristiques par la mise en oeuvre de plus scénarios applicatifs. / The Internet of Things (IoT) aims to create a global ubiquitous ecosystem composed of large numbers of heterogeneous devices. To achieve this vision, the World Wide Web is emerging as a suitable candidate to interconnect IoT devices and services at the application layer into a Web of Things (WoT).However, the WoT is evolving towards large silos of things, and thus the vision of a global ubiquitous ecosystem is not fully achieved. Furthermore, even if the WoT facilitates mashing up heterogeneous IoT devices and services, existing approaches result in static IoT mashups that cannot adapt to dynamic environments and evolving user requirements. The latter emphasizes another well-recognized challenge in the IoT, that is enabling people to interact with a vast, evolving, and heterogeneous IoT.To address the above limitations, we propose an architecture for an open and self-governed IoT ecosystem composed of people and things situated and interacting in a global environment sustained by heterogeneous platforms. Our approach is to endow things with autonomy and apply the social network metaphor to createflexible networks of people and autonomous things. We base our approach on results from multi-agent and WoT research, and we call the envisioned IoT ecosystem the Social Web of Things.Our proposal emphasizes heterogeneity, discoverability and flexible interaction in the IoT. In the same time, it provides a low entry-barrier for developers and users via multiple layers of abstraction that enable them to effectively cope with the complexity of the overall ecosystem. We implement several application scenarios to demonstrate these features.

Sensors are widely deployed in our environment, and their number is increasing rapidly. In the near future, billions of devices will all be connected to each other, creating an Internet of Things. Furthermore, computational intelligence is needed to make applications involving these devices truly exciting. In IoT, however, the vast amounts of data will not be statically prepared for batch processing, but rather continually produced and streamed live to data consumers and intelligent algorithms. We refer to applications that perform live analysis on live data streams, bringing intelligence to IoT, as the Analysis of Things. However, the Analysis of Things also comes with a new set of challenges. The data sources are not collected in a single, centralized location, but rather distributed widely across the environment. AoT applications need to be able to access (consume, produce, and share with each other) this data in a way that is natural considering its live streaming nature. The data transport mechanism must also allow easy access to sensors, actuators, and analysis results. Furthermore, analysis applications require computational resources on which to run. We claim that system support for AoT can reduce the complexity of developing and executing such applications. To address this, we make the following contributions: - A framework for systems support of Live Streaming Analysis in the Internet of Things, which we refer to as the Analysis of Things (AoT), including a set of requirements for system design - A system implementation that validates the framework by supporting Analysis of Things applications at a local scale, and a design for a federated system that supports AoT on a wide geographical scale - An empirical system evaluation that validates the system design and implementation, including simulation experiments across a wide-area distributed system We present five broad requirements for the Analysis of Things and discuss one set of specific system support features that can satisfy these requirements. We have implemented a system, called \textsubscript{SS}IoTa, that implements these features and supports AoT applications running on local resources. The programming model for the system allows applications to be specified simply as operator graphs, by connecting operator inputs to operator outputs and sensor streams. Operators are code components that run arbitrary continuous analysis algorithms on streaming data. By conforming to a provided interface, operators may be developed that can be composed into operator graphs and executed by the system. The system consists of an Execution Environment, in which a Resource Manager manages the available computational resources and the applications running on them, a Stream Registry, in which available data streams can be registered so that they may be discovered and used by applications, and an Operator Store, which serves as a repository for operator code so that components can be shared and reused. Experimental results for the system implementation validate its performance. Many applications are also widely distributed across a geographic area. To support such applications, \textsubscript{SS}IoTa must be able to run them on infrastructure resources that are also distributed widely. We have designed a system that does so by federating each of the three system components: Operator Store, Stream Registry, and Resource Manager. The Operator Store is distributed using a distributed hast table (DHT), however since temporal locality can be expected and data churn is low, caching may be employed to further improve performance. Since sensors exist at particular locations in physical space, queries on the Stream Registry will be based on location. We also introduce the concept of geographical locality. Therefore, range queries in two dimensions must be supported by the federated Stream Registry, while taking advantage of geographical locality for improved average-case performance. To accomplish these goals, we present a design sketch for SkipCAN, a modification of the SkipNet and Content Addressable Network DHTs. Finally, the fundamental issue in the federated Resource Manager is how to distributed the operators of multiple applications across the geographically distributed sites where computational resources can execute them. To address this, we introduce DistAl, a fully distributed algorithm that assigns operators to sites. DistAl also respects the system resource constraints and application preferences for performance and quality of results (QoR), using application-specific utility functions to allow applications to express their preferences. DistAl is validated by simulation results.

GPS is widely used for localization and tracking, however traditional GPS receivers consume too much energy for many applications. This thesis implements and evaluates the performance of a low energy GPS solution, including a working hardware prototype, that reduces energy consumption significantly. The prototype operates for 2 years on a coin cell battery, sampling every minute. The corresponding time for a traditional receiver is 2 days. The main difference is that a traditional receiver requires 30 seconds of data to estimate a position; this solution only requires 2 milliseconds of data, a reduction of a factor 15 000. The solution consists of a portable device, sampling the GPS signal, and server software that utilizes Doppler navigation and Coarse Time Navigation to estimate positions. The median positioning error is at most 38 meters in our tests. We expect that this solution will enable positioning for billions of devices in the near future.

The Internet of Things (IoT) is a vision that aims at inter-connecting every physical identifiable object (or, a thing) via a global networking infrastructure (e.g., the legacy Internet). Several architectures are proposed to realize this vision; many of which agree that the IoT shall be considered as a global network of networks. These networks are used to manage wireless sensors, Radio Frequency IDentification (RFID) tags, RFID readers and other types of electronic devices and integrate them into the IoT. A major requirement of the IoT architectures is scalability, which is the capability of delivering high performance even if the input size (e.g., number of the IoT objects) is large. This thesis studies and proposes solutions to meet this requirement, and specifically focuses on the scalability issues found in the networks of the IoT. The thesis proposes several network formation algorithms to achieve these objectives, where a network formation algorithm is an algorithm that, if applied to a certain network, optimizes it to perform its tasks in a more efficient manner by virtually deleting some of its nodes and/or edges. The thesis focuses on three types of networks found in the IoT: 1) RFID readers coverage networks; whose main task is to cover (i.e., identify, monitor, track, sense) IoT objects located in a given area, 2) readers inter-communications networks; whose main task is to guarantee that their nodes are able to inter-communicate with each other and hence use their resources more efficiently (the thesis specifically considers inter-communication networks of readers using Bluetooth for communications), and 3) Object Name Systems (ONS) which are networks of several inter-connected database servers (i.e., distributed database) whose main task is to resolve an object identifier into an Internet address to enable inter-communication via the Internet. These networks are chosen for several reasons. For example, the technologies and concepts found in these networks are among the major enablers of the IoT. Furthermore, these networks solve tasks that are central to any IoT architecture. Particularly, the thesis a) studies the data and readers redundancy problem found in RFID readers coverage networks and introduces decentralized RFID coverage and readers collisions avoidance algorithms to solve it, b) contributes to the problem of forming multihop inter-communications networks of Bluetooth-equipped readers by proposing decentralized time-efficient Bluetooth Scatternet Formation algorithms, and c) introduces a geographic-aware ONS architecture based on Peer-To-Peer (P2P) computing to overcome weaknesses found in existing ONS architectures.

Les villes contemporaines font face à de nombreux enjeux : énergétiques,écologiques, démographiques ou encore économiques. Pour y répondre, des moyens technologiques sont mis en place dans les villes via l’utilisation de capteurs et d’actionneurs. Ces villes sont dites intelligentes.Actuellement, les villes intelligentes sont opérés des acteurs qui ne partagent ni leurs données de capteurs ni l’accès à leurs actionneurs.Cette situation est dite verticale : chaque opérateur déploie ses propres capteurs et actionneurs et possède sa propre infrastructure informatique hébergeant ses applications. Cela conduit à une redondance de l’infrastructure et à des applications ad-hoc pour superviser et contrôler un domaine de la ville.Une tendance est d’aller vers une situation dite horizontale via l’utilisation d’une plateforme de médiation ouverte et partagée. Les données de capteurs et les accès aux actionneurs sont mutualisés au sein de ce type de plateforme, permettant leur partage entre les différents acteurs. Les coûts d’infrastructure et de développement s’en trouvent alors réduits.Cette thèse s’inscrit dans ce contexte d’horizontalisation, au sein d’une plate- forme ouverte et partagée, dans laquelle nous proposons :1) une couche d’abstraction pour le contrôle et la supervision de la ville, 2) un mécanisme de contrôle de concurrence gérant les cas de conflits, 3) un mécanisme de coordination favorisant la réutilisation des actionneurs, 4) une implémentation de notre travail par une preuve de concept.L’abstraction que nous proposons se base sur des modèles issus des systèmes réactifs. Ils ont pour objectif d’être générique et représente l’invariant de la ville intelligente : les éléments physiques. Ils permettent aux applications de contrôler et superviser la ville.Pour faciliter le développement d’applications nous uniformisons l’interface de nos modèles. Ces applications pouvant avoir des contraintes temps réel, particulièrement celles qui ont des objectifs de contrôle, nous proposons de tirer parti de l’architecture distribuée de ce type de plateforme.Compte-tenu du partage des actionneurs, nous avons identifié que des conflits peuvent survenir entre les applications. Nous proposons un mécanisme de contrôle de concurrence pour traiter ces cas de conflits.Nous avons également identifié qu’un mécanisme de coordination doit être offert aux applications souhaitant effectuer atomiquement des opérations de contrôle. Un tel mécanisme favorise la réutilisation des actionneurs présents dans la ville.Enfin, nous avons implémenté nos propositions autour d’une preuve de concept, comprenant plusieurs cas d’usages, permettant de démontrer notre travail. / Nowadays cities face several challenges and are concerned by ecological, energetic, economical, and demographical aspects. Smart cities, equipped with sensors, actuators, and digital infrastructures, are meant to tackle these issues.Current smart cities are operated by several actors without sharing sensor data or accesses to the actuators. This is a vertical organization, in which each actor deploys its own sensors and actuators, and manages its own digital infrastructure. Each actor may be interested in a different aspect of city management, for instance traffic management, air control, etc. The current trend is a transition towards a more horizontal organization, based on an open and shared mediation platform. In such a platform, sensor data and accesses to actuators can be shared among several actors. The costs related to nfrastructure deployment and management are therefore reduced for each individual actor. This PhD is a contribution to this volution towards horizontal organizations, with open and shared platforms. We propose: (1) an abstraction layer for the ontrol and supervision of the city; (2) a concurrency management mechanism; (3) a coordination mechanism that helps haring actuators; (4) a proof-of-concept implementation of these contributions. The abstraction layer we propose helps users control and supervise a city. It is based upon formal models inspired by the ones used in the programming of reactive systems. They represent the physical elements present in each smart city, with genericity principles. In order to ease application development, the interface of those models is made uniform. Since applications, especially control ones, may ave real-time constraints, we also list the constraints this poses on distributed infrastructures. As soon as actuators are shared, conflicts may occur between users. Our proposals include a concurrency management mechanism, based on eservation principles. We also provide a coordination mechanism for the users to be able to perform several actions in an tomic way.All these principles have been implemented as a proof of concept. We review several use cases, to demonstrate he potential benefits of our proposals.

Dans le contexte de l'Internet des Objets (IoT), on estime à plus de 10% la proportion de connections réalisées via les réseaux longue portée bas débit, représentant ainsi plusieurs milliards d’objet connectés. Afin de satisfaire les exigences en termes de sensibilité et de réduction du débit, deux approches sont généralement envisagées : l’approche bande étroite, et l’approche faible efficacité spectrale. En comparant les performances des systèmes existants à la limite théorique issue de la théorie de l'information et démontrée par Shannon, on constate qu’un gain en performance est atteignable, tout en travaillant toujours à de faibles niveaux de sensibilité. La théorie de l'information permet d'affirmer qu'un compromis entre l'efficacité spectrale et l'efficacité énergétique doit toujours être fait. Ainsi, une haute efficacité énergétique s'obtiendra au détriment d'une efficacité spectrale faible. A l'inverse, un système fonctionnant à une haute efficacité spectrale devra utiliser plus d'énergie pour transmettre le même nombre de bits et atteindre le même taux d'erreur.Ce travail s’intéresse à l’approche faible efficacité spectrale. En partant des modulations orthogonales, qui permettent d’atteindre la limite théorique de Shannon à des efficacités spectrales très faibles, et des processus turbo, qui atteignent d’excellentes performances à des efficacités spectrales élevées, l’utilisation conjointe d’une modulation orthogonale et d'un code correcteur associés à un récepteur itératif dans une technique dénommée Turbo-FSK est étudiée. Les différents paramètres de la technique sont optimisés en utilisant un outil classique des processus itératifs, l’Extrinsic Information Transfer (EXIT) chart. Les performances mesurées démontrent que la technique permet bien d’atteindre de très faibles niveaux de sensibilité et répond aux critères des réseaux longue portée bas débit. Cependant, la technique ne dispose de point de fonctionnement qu’à de très faibles valeurs d’efficacité spectrale : pour certaines applications ou si la portée nécessaire est réduite, il peut être bénéfique pour le système d’augmenter son efficacité spectrale. Ceci est rendu possible grâce à l’introduction d’une composante linéaire dans l’alphabet de modulation et d’un mécanisme de poinçonnage spécifique à la technique dans une version flexible appelée Coplanar Turbo-FSK. L’étude de l’influence des paramètres et des performances sur un canal à bruit blanc additif gaussien permet en effet de conclure sur la flexibilité de l’efficacité spectrale du système, tout en fonctionnant proche de la limite théorique. Finalement, l’étude jusqu’ici théorique est étendue à un contexte plus pratique, où des canaux sélectifs en fréquences sont considérés. Une encapsulation du système utilisant une architecture OFDM est considérée, et différentes mesures caractéristiques des systèmes de télécommunication sont évaluées. Les résultats sont confrontés à la solution Narrow-Band IoT proposée par l’organisme 3GPP et démontrent ici encore le potentiel de la solution Turbo-FSK pour les réseaux longue portée bas débit. / More than 10% of the Internet-of-Things (IoT) connections are expected to be realized through Low Power Wide Area (LPWA) networks, representing several billions of connected devices. Several industrial solutions have been developed and a standardization process is ongoing. The low levels of sensitivity and low data rate required for the long range communication are achieved by the means of two strategies: a narrow-band strategy and a low spectral efficiency strategy. Considering the limits of the information theory, additional gains in the communication's energy efficiency can be achieved. Nonetheless, a trade-off between spectral efficiency and energy efficiency should always be made. Reliable transmission with high energy efficiency will necessarily result in poor spectral efficiency, and in comparison, a system with a higher spectral efficiency has to consume more energy to transmit the same amount of bits with the same arbitrary level of error.This work considers the low spectral efficiency strategy. The combination of orthogonal modulations and a powerful channel code is studied. The scheme, so-called Turbo-FSK, associates the low spectral efficiency of Frequency Shift Keying (FSK) with the energy efficiency gain of a turbo receiver. Low levels of spectral efficiency can be achieved while optimizing the use of the available resource. The parameters of the scheme are optimized using a classic tool for iterative receivers, the Extrinsic Information Transfer (EXIT) chart. Performance of Turbo-FSK compared to existing LPWA solutions demonstrates the potential of the proposed solution to achieve low levels of sensitivity and to outperform existing schemes. However, the restrictions on low levels of spectral efficiency reduces the number of possible applications for the scheme. By introducing a linear component in the alphabet and a puncturing procedure, flexibility in spectral efficiency is achieved. A large range of spectral efficiencies can be obtained while maintaining performance close to the channel capacity theoretical limit. Eventually, more practical scenarios are considered for evaluating the performance of the scheme. Frequency selective channels are considered and an encapsulation in a Fast Fourier Transform (FFT) based system is implemented. Various indicators are studied and the Turbo-FSK scheme is compared to well-known technologies, such as schemes using Orthogonal Frequency Division Multiplexing (OFDM) associated with a powerful Forward Error Correction (FEC) scheme, namely Turbo Code (TC).

With the emergence of connected and autonomous vehicles, sensors are increasingly deployed within car. Traffic generated by these sensors congest traditional intra-vehicular networks, such as CAN buses. Furthermore, the large amount of wires needed to connect sensors makes it hard to design cars in a modular way. These limitations have created impetus to use wireless technologies to support intra-vehicular communication. In this dissertation, we tackle the challenge of designing and evaluating data collection protocols for intra-car networks that can operate reliably and efficiently under dynamic channel conditions. First, we evaluate the feasibility of deploying an intra-car wireless network based on the Backpressure Collection Protocol (BCP), which is theoretically proven to be throughput-optimal. We uncover a surprising behavior in which, under certain dynamic channel conditions, the average packet delay of BCP decreases with the traffic load. We propose and analyze a queueing-theoretic model to shed light into the observed phenomenon. As a solution, we propose a new protocol, called replication-based LIFO-backpressure (RBL). Analytical and simulation results indicate that RBL dramatically reduces the delay of BCP at low load, while maintaining its high throughput performance. Next, we propose and implement a hybrid wired/wireless architecture, in which each node is connected to either a wired interface or a wireless interface or both. We propose a new protocol, called Hybrid-Backpressure Collection Protocol (Hybrid-BCP), for the intra-car hybrid networks. Our testbed implementation, based on CAN and ZigBee transceivers, demonstrates the load balancing and routing functionalities of Hybrid-BCP and its resilience to DoS attacks. We further provide simulation results, obtained based on real intra-car RSSI traces, showing that Hybrid-BCP can achieve the same performance as a tree-based protocol while reducing the radio transmission power by a factor of 10. Finally, we present TeaCP, a prototype Toolkit for the evaluation and analysis of Collection Protocols in both simulation and experimental environments. TeaCP evaluates a wide range of standard performance metrics, such as reliability, throughput, and latency. TeaCP further allows visualization of routes and network topology evolution. Through simulation of an intra-car WSN and real lab experiments, we demonstrate the functionality of TeaCP for comparing different collection protocols.

Orientador: Prof. Dr. João Henrique Kleinschmidt / Dissertação (mestrado) - Universidade Federal do ABC, Programa de Pós-Graduação em Engenharia da Informação, 2015. / Na Internet das Coisas os objetos físicos têm um componente virtual capaz de prover ou requisitar determinados serviços. É uma tendência que trará vantagens sem precedentes para a automação de processos e diversas aplicações. A análise de modelos de gerenciamento de confiança para IoT para detectar comportamentos maliciosos tem recebido poucas contribuições da comunidade científica. Alguns pesquisadores trataram desta questão, mas poucos trabalhos analisam os requisitos para a correta implementação da IoT. O objetivo desta dissertação é identificar o comportamento malicioso de nós e prevenir possíveis ataques que interrompam os serviços da rede. Neste trabalho são feitas diferentes abordagens para pesquisar um modelo de gerenciamento de confiança capaz de caracterizar o comportamento dos nós. O modelo proposto usa informações diretas geradas pelas comunicações entre os nós e recomendações de outros nós para calcular a confiança. Usa uma abordagem multi-serviço em que cada nó provê diversos serviços para os outros nós da rede. A habilidade de um nó em prover um serviço é recompensada, enquanto que um nó que não forneça um serviço corretamente é punido. Cada nó tem uma tabela de confiança dos seus vizinhos, que pode ser compartilhada com os outros nós como recomendações. A abordagem distribuída permite que os nós sejam completamente autônomos em tomar decisões sobre o comportamento dos nós. A avaliação de confiança dos nós é um meio efetivo de encorajar a colaboração na rede e ao mesmo tempo melhorar a segurança em redes distribuídas. Três ataques são testados para verificar a validade do modelo de confiança: ataque On-Off, ataque Seletivo e Bad mouthing. O modelo de gerenciamento de confiança foi implementado no Contiki, um sistema operacional desenvolvido para IoT e redes de sensores. Extensivas simulações foram feitas no simulador Cooja-Contiki para ilustrar os ataques e avaliar o desempenho do modelo proposto. Os resultados de simulação mostram que o modelo tem um bom desempenho em detectar os nós maliciosos. / In Internet of Things (IoT), the physical objects have a virtual component able to provide or require determined services. It is a trend that will bring unprecedented advantages to the process automation. The analysis of the trust management models for IoT to detect the malicious behavior on the network, has been undervalued and with little scientific contribution in the academic field. In spite of researchers has already addressed the issue, only few give a theoretic analysis on the requirements for the proper implementation of IoT. The purpose of this thesis work is to identify the malicious behavior of the nodes and prevent possible attacks that disrupt entire network to IoT context. In this thesis different approaches are followed to investigate a lightweight model of trust management able to characterize the behavior of the nodes with little effort. Our model use direct information generated from direct communication of nodes and recommendations of the others nodes to evaluate the trust. We use a multi-service approach where each node provides several services to others node. The ability to provide a service is rewarded and, punished when it is not provided. In our trust model each node has a trust table of their neighbors in the same radio coverage, which will be shared to others nodes as recommendations. This distributed approach allows nodes to be completely autonomous in making decisions about the behavior of other nodes. The trust evaluation of nodes is an effective method to encourage the collaboration on the network and at the same time to improve network security in distributed networks. In this thesis work, we present three attacks that can undermine the accuracy of trust evaluation. Based on our investigation on attacks and defense, we designed and implemented a trust management model based on the construction of Contiki, an operating system developed for IoT and sensor networks. Extensive simulations were performed using COOJA-Contiki to illustrate On-OFF attack, Selective attack and Bad mouthing attack, the effectiveness of the techniques used, and the overall performance of the proposed trust model. Simulation results shows effectiveness against these attacks and also a good performance to recognize the malicious nodes especially to the Bad mouthing attack when are used direct information and recommendations wherein is obtained a reduction time compared when is used only the direct information.