In this study, we study the dynamics of network adaptive video streaming and propose novel algorithms for rate distortion control in video streaming. While doing so, we maintain inter-protocol fairness with TCP (Transmission Control Protocol) that is the dominant transport protocol in the current Internet. The proposed algorithms are retransmission-based and necessitate the use of playback buffers in order to tolerate the extra latency introduced by retransmissions. In the first part, we propose a practical network-adaptive streaming scheme based on TCP transport and the idea of Selective Frame Discarding (SFD) that makes use of two-layer temporally scalable video. The efficacy of the SFD scheme is validated for playout buffer times in the order of seconds and therefore makes it suitable more for delay tolerant streaming applications. In the second part of the thesis, we propose an application layer rate-distortion control algorithm which provides Optimal Scheduling and Rate Control (OSRC) policies in the average reward sense in order to achieve efficient streaming of video. The Optimal Scheduling (OS) we propose maximizes the probability of successfully on time delivery according to a prespecified set of rate constraints, and different channel conditions by using Markov Decision Process (MDP) models. On the other hand optimal rate control (RC) is achieved by calculating the optimal rate constraint which minimizes the average distortion of a video streaming session by making use of the video distortion model derived for lossy channels and achievable success probabilities provided by the set of optimal schedules. For numerical examples, we focus on an equation-based TCP friendly rate control (TFRC) protocol where transport layer retransmissions are disabled and Fine Granular Scalable (FGS) coded video is used for improved rate adaptation capabilities but with an additional rate distortion penalty. The efficacy of the proposed OSRC algorithm is demonstrated by means of both analytical results and ns-2 simulations.

This thesis is concerned with the sampled-data control of non-linear continuous-time systems. Sampled-data systems are present in all computer controlled, hybrid or embedded systems. The design and computation of suitable digital controllers represent unavoidable tasks since both continuous and discrete-time components interact. The basic framework of this work takes part of a wide research activity performed by S. Monaco and D. Normand-Cyrot regarding non-linear sampled-data systems. The underlying idea is to design digital controllers that recover certain continuous-time properties that are usually degraded through sampling as it is the case when continuous-time controllers are implemented by means of zero-order holder devices (emulated control). This thesis brings contributions into three different directions. The first one regards theoretical developments: a new digital backstepping-like strategy design for strict-feedback systems is proposed. This method is compared with other strategies proposed in the literature. The second contribution is the development of a control designer and of a simulation toolbox (in Matlab) for non-linear sampled-data systems. This toolbox includes different digital design strategies such as: multi-rate control, input-output/Lyapunov matching, digital backstepping design, etc. The third contribution concerns several case studies conducted to highlight the performances of the sampled-data controller designs, computed by the means of the software toolbox. Experimental and simulation results are described for various real examples especially in the area of electrical and mechanical processes.

Esta dissertação de mestrado apresenta um novo esquema de controle de taxa hierárquico – HRC – para o padrão MVC – extensão para vídeos de múltiplas vistas do padrão H.264 – com objetivo de melhorar o aproveitamento da largura de banda oferecida por um canal entregando o vídeo comprimido com a melhor qualidade possível. Este esquema de controle de taxa hierárquico foi concebido para controlar de forma conjunta os níveis de quadro e de unidades básicas (BU). O esquema proposto explora a correlação existente entre as distribuições das taxas de bits em quadros vizinhos para predizer de forma eficiente o comportamento dos futuras bitrates através da aplicação de um controle preditivo baseado em modelos – MPC – que define uma ação de controle apropriada sobre as ações de adaptação do parâmetro de quantização (QP). Para prover um ajuste em granularidade fina, o QP é adicionalmente adaptado internamente para cada quadro por um processo de decisão de Markov (MDP) implementado em nível de BU capaz de considerar mapas com Regiões de Interesse (RoI). Um retorno acoplado aos dois níveis supracitados é realizado para garantir a consistência do sistema. Aprendizagem por Reforço é utilizada para atualizar os parâmetros do Controle Preditivo baseado em Modelos e do processo de decisão de Markov. Resultados experimentais mostram a superioridade da utilização do esquema de controle proposto, comparado às soluções estado-da-arte, tanto em termos de precisão na alocação de bits quanto na otimização da razão taxa-distorção, entregando um vídeo de maior qualidade visual nos níveis de quadros e de BUs. / This master thesis presents a novel Hierarchical Rate Control – HRC – for the Multiview Video Coding standard targeting an increased bandwidth usage and high video quality. The HRC is designed to jointly address the rate control at both framelevel and Basic Unit (BU)-level. This scheme is able to exploit the bitrate distribution correlation with neighboring frames to efficiently predict the future bitrate behavior by employing a Model Predictive Control that defines a proper control action through QP (Quantization Parameter) adaptation. To provide a fine-grained tuning, the QP is further adapted within each frame by a Markov Decision Process implemented at BU-level able to take into consideration a map of the Regions of Interest. A coupled frame/BU-level feedback is performed in order to guarantee the system consistency. A Reinforcement Learning method is responsible for updating the Model Predictive Control and the Markov Decision Process parameters. Experimental results show the superiority of the Hierarchical Rate Control compared to state-of-the-art solutions, in terms of bitrate allocation accuracy and rate-distortion, while delivering smooth video quality at both frame and Basic Unit levels.

La technique MIMO (Multiple-Input Multiple-Output) est l’une des techniques de base qui offre une diversité spatiale. Elle associe plusieurs antennes à l’émission et à la réception. En plus de la diversité spatiale, le système MIMO permet d’augmenter le gain de multiplexage sans avoir besoin de plus de bande passante ou de puissance d’émission. Cependant, la technique MIMO a des limites liées au coût d’installation de plusieurs antennes sur un terminal, et a l’écart minimal exigé entre les antennes. La communication coopérative a été proposée comme une technologie alternative, dans laquelle la diversité spatiale peut être réalisée en coordonnant plusieurs nœuds qui sont proches géographiquement pour former des réseaux d’antennes virtuelles. La coopération permet de lutter contre l’instabilité du canal radio et de faire face aux phénomènes qui le perturbent comme les évanouissements, les bruits, ou les interférences. Elle permet aussi d’améliorer les performances du système en termes de débit global, d’énergie consommée et d’interférences, etc. Dans le cadre des communications coopératives, nous avons proposé deux protocoles MAC coopératifs dans le contexte des réseaux ad hoc. La première proposition est le protocole RACT (Rate Adaptation with Cooperative Transmission). Ce protocole combine la coopération avec un mécanisme d’adaptation de débit. Lorsqu’un lien entre une source et une destination subit de mauvaises conditions de canal, une station relais est sélectionnée dans le voisinage des deux nœuds de sorte que la liaison directe à faible débit de transmission soit remplacée par un lien à deux sauts avec un débit de données plus élevé. La sélection du meilleur relais est fondée sur un processus de contention distribué. La procédure ne nécessite aucune connaissance de la topologie et aucune communication entre les relais potentiels. Lorsque la qualité de la liaison directe est bonne et que la transmission coopérative n’est pas nécessaire, le protocole fonctionne comme un mécanisme d’adaptation de débit. L’adaptation de débit de données est également réalisée sans aucune signalisation supplémentaire. La sélection du meilleur relais et l’adaptation de débit sont fondés sur des mesures instantanées du canal pour s’adapter aux conditions dynamiques du canal radio. Dans le but d’améliorer davantage les performances du système, nous avons proposé notre deuxième protocole MAC coopératif PRACT (Power and Rate Adaptation with Cooperative Transmission). Ce protocole combine un mécanisme d’adaptation de puissance et de débit (TPRC : Transmit Power and Rate Control) avec un mécanisme de coopération. C’est en cela que cette contribution se distingue des solutions proposées dans la littérature. Notre objectif avec cette contribution est d’atteindre une efficacité d’énergie pour la transmission des données tout en augmentant le débit global du réseau. PRACT propose d’ajuster dynamiquement la puissance et le débit de transmission en s’adaptant aux variations de la qualité du canal radio. Cela permet de gagner davantage dans l’énergie économisée. En outre, le contrôle de puissance, réduit les interférences et augmente la réutilisation spatiale entre cellules ad hoc adjacentes en utilisant la même fréquence de transmission. L’idée de base du protocole est de permettre à chaque nœud dans le réseau ad hoc de créer une table avec les combinaisons puissance-débit optimales, en se fondant seulement sur les spécifications de la carte réseau, à savoir, les débits de transmission possible et la consommation en énergie de la carte. Avec la connaissance des qualités des liens obtenue grâce à l’échange des trames de contrôle et en recherchant dans la table puissance-débit, les nœuds choisissent la stratégie de transmission la plus adaptée pour chaque transmission de trames de données, ainsi que le mode de transmission (direct ou coopératif). / MIMO (Multiple-Input Multiple-Output) technology is one of the basic techniques that offer a spatial diversity. It combines multiple antennas for transmission and reception. In addition to spatial diversity, MIMO can increase the multiplexing gain without requiring more bandwidth or transmit power. However, the MIMO technology has limitations related to the cost of installing multiple antennas on a terminal, and to the minimum distance required between antennas. The cooperative communication has been proposed as an alternative technology, in which the spatial diversity can be achieved by coordinating multiple nodes that are geographically close to form virtual antenna arrays. Cooperation helps to fight against the instability of the radio channel and deal with phenomena that disturb this channel like fading, noise or interference. It also improves system performance in terms of overall throughput, energy consumption and interference, etc. In the context of cooperative communications, we proposed two MAC protocols in the context of cooperative ad-hoc networks. The first proposal is the RACT (Rate Adaptation with Cooperative Transmission) protocol. This protocol combines cooperation with a rate adaptation mechanism. When a link between a source and a destination suffers from poor channel conditions, a relay station is selected in the neighborhood of the two nodes so that the direct low data-rate link is replaced by a two-hop link with a higher data-rate. Selecting the best relay is based on a distributed contention process. The procedure requires no knowledge of the topology and no communication between the potential relay. When the quality of the direct link is good enough and the cooperative transmission is not necessary, the protocol operates as a rate adaptation mechanism. The data rate adaptation is also performed without any additional signaling. Both the best relay selection and the rate adaptation is based only on the instantaneous channel measurements to adapt to the dynamic conditions of the radio channel. In order to further improve the system performance, we proposed our second cooperative MAC protocol PRACT (Power and Rate Adaptation with Cooperative Transmission). This protocol combines a power and rate control mechanism (TPRC: Transmit Power and Rate Control) with a mechanism for cooperation, this feature distinguishes this contribution from the solutions proposed in the literature. Our objective with this contribution is to achieve energy efficiency for data transmission while increasing the overall throughput of the network. PRACT proposes to dynamically adjust dynamically the power and the transmission rate to adapt to the radio channel quality variations. This way more energy can be saved. In addition, the power control reduces interference and increases the spatial reuse between adjacent ad-hoc cells using the same channel transmission frequency. The basic idea of the protocol is to allow each node in the network to create a table with the best power-rate combinations, based only on the specifications of the network card, namely the possible transmission rates, transmit power levels and the power consumption of the card. With the knowledge of the qualities of links obtained through the exchange of the control frames and looking up in the power-rate table, the nodes choose the most suitable transmission strategy, for each data frame transmission, and the transmission mode (direct or cooperative).

Submitted by RAUL KATAYAMA MANSANO null (rkmansano@yahoo.com.br) on 2016-11-04T01:12:57Z No. of bitstreams: 1 Dissertação Raul Katayama Mansano.pdf: 4167710 bytes, checksum: 35cc706c4a721f9334825773f9f2ff77 (MD5) / Approved for entry into archive by Juliano Benedito Ferreira (julianoferreira@reitoria.unesp.br) on 2016-11-10T13:57:40Z (GMT) No. of bitstreams: 1 mansano_rk_me_bauru.pdf: 4167710 bytes, checksum: 35cc706c4a721f9334825773f9f2ff77 (MD5) / Made available in DSpace on 2016-11-10T13:57:40Z (GMT). No. of bitstreams: 1 mansano_rk_me_bauru.pdf: 4167710 bytes, checksum: 35cc706c4a721f9334825773f9f2ff77 (MD5) Previous issue date: 2016-09-09 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES) / Com os recentes avanços das tecnologias sem fio e a proliferação de sensores sem fio, há um crescente interesse na implementação de Sistemas Controle via Redes Sem Fio (WNCSs), que fornecem vantagens em relação às arquiteturas tradicionais ponto-a-ponto e às arquiteturas de redes cabeadas. Apesar das vantagens, a inserção de redes industriais na malha de controle impõe não-linearidades e restrições que afetam o desempenho e a estabilidade do WNCS. Além disto, uma questão fundamental para aplicações de WNCS é a vida útil da bateria de alimentação dos sensores sem fio, uma vez que é uma fonte limitada de energia. Como a transmissão da informação na rede sem fio requer um alto gasto energético pelo dispositivo, deve-se restringir a quantidade de comunicações para poupar bateria. Esta restrição inviabiliza o uso de sensores sem fio em diversas aplicações de WNCS. Neste contexto, este trabalho apresenta o desenvolvimento de um controlador adaptativo multi-rate para eficiência energética em aplicações industriais de WNCSs, através da diminuição da frequência de transmissão de dados na rede e, portanto, redução do consumo energético dos dispositivos sem fio. Um controlador adaptativo auto-ajustável foi implementado para identificar o modelo do WNCS, simular tal modelo e sintonizar os parâmetros do controlador a cada passo de controle, fornecendo robustez contra distúrbios e não-linearidades inerentes ao WNCS. O diferencial do controlador adaptativo é a incorporação das técnicas de identificação por pacote e de controle multi-rate. A técnica de identificação por pacote consiste em transmitir mensagens com vários dados (não somente o mais atual) coletados durante o período de amostragem do sensor sem fio, melhorando a identificação do modelo do WNCS e, consequentemente, o desempenho do controlador adaptativo. A técnica de controle multi-rate consiste em usar dados virtuais de realimentação, provenientes do modelo simulado do WNCS, para possibilitar uma atuação sobre o processo a uma frequência mais rápida que a amostragem dos sensores sem fio, permitindo a redução das transmissões sem fio do WNCS. Resultados experimentais mostram que o controlador adaptativo multi-rate é robusto e efetivo para aplicações de WNCS, permitindo poupar energia das baterias dos sensores sem fio sem prejudicar significativamente o desempenho de controle do WNCS. As análises do impacto do período de amostragem e do parâmetro Γ do controlador permitiram a obtenção de valores ótimos para a melhoria da eficiência energética do WNCS. / Recent advances in wireless technologies and the proliferation of wireless sensors led to an increasing interest in the implementation of Wireless Networked Control Systems (WNCS), which provide advantages over traditional peer-to-peer and cabled networks architectures. Despite these advantages, inserting a communication network in the control loop impose nonlinearities and constraints which affect stability and performance of the system. Furthermore, a major issue in wireless applications is the lifetime of the sensors batteries, which are a limited source of power. As transmitting data over the network requires high-energy expenditure, it is imperative to reduce the number of communications, in order to save battery. This constraint makes it unfeasible to use wireless sensors in most WNCS applications. In this context, this work aims to develop a multi-rate adaptive controller to enhance energy efficiency in industrial WNCS applications, by reducing frequency of data transmission over the network, thus reducing power expenditure of the wireless devices. A self-tuning adaptive controller is implemented, which can identify the WNCS model, simulate such model and tune the controller parameters at each control step, then providing robustness to disturbance and inherent nonlinearities of the WNCS. The adaptive controller is augmented with a multi-rate control technique and packet-based identification. The packet-based identification consists in transmitting messages with a pack of data (instead of only transmitting the most recent one) sampled during the inter-samples period, thus improving identification of the WNCS model and, consequently, improving control performance. The multi-rate control technique consists in using virtual feedback data, provided by the simulated model of the WNCS, then enabling actuation faster than wireless sampling, allowing the reduction of wireless transmissions in the WNCS. Experimental results show that the implemented multi-rate adaptive controller is robust and effective to WNCS and improve battery lifetime without decreasing control performance of the WNCS significantly. By investigating the impacts of sampling period and of controller parameter Γ determined optimized values to improve energy efficiency of the WNCS.

Submitted by Felipe Fakir null (zafakir@yahoo.com.br) on 2017-06-27T07:01:28Z No. of bitstreams: 1 FFAKIR Dissertação vFinalFichaCataAta.pdf: 2064786 bytes, checksum: 158a935a636b9dbf9e59618a35b4c8ef (MD5) / Approved for entry into archive by Luiz Galeffi (luizgaleffi@gmail.com) on 2017-06-28T19:39:58Z (GMT) No. of bitstreams: 1 fakir_f_me_bauru.pdf: 2064786 bytes, checksum: 158a935a636b9dbf9e59618a35b4c8ef (MD5) / Made available in DSpace on 2017-06-28T19:39:58Z (GMT). No. of bitstreams: 1 fakir_f_me_bauru.pdf: 2064786 bytes, checksum: 158a935a636b9dbf9e59618a35b4c8ef (MD5) Previous issue date: 2017-06-01 / A tecnologia de comunicação wireless vem se tornando parte fundamental do cotidiano das indústrias de processos, onde o uso de transmissores wireless aplicados à monitoração e controle já é uma realidade. A arquitetura de Sistema de Controle via Rede Sem Fio (WNCS) possui vantagens em relação às arquiteturas tradicionais ponto-a-ponto e às arquiteturas de redes cabeadas devido à facilidade de instalação, configuração e manutenção. No entanto, a evolução desta tecnologia introduziu novos desafios para a implementação da malha de controle fechada por um instrumento wireless como as não linearidades, perda de pacote de dados e restrições da comunicação de dados nas redes sem fio. Outro fator crítico relacionado à implementação de WNCSs é a fonte de energia limitada destes transmissores, que possuem vida útil dependente da quantidade de acessos e dados transmitidos. Este trabalho apresenta o estudo e o desenvolvimento de um controlador preditivo multi-rate como alternativa para melhorar a eficiência energética em aplicações industriais de WNCSs. A estratégia proposta não necessita receber constantemente os valores reais das variáveis do processo transmitidos pelos transmissores wireless, pois o controlador preditivo baseado em modelo (MPC) se utiliza do submodelo interno das variáveis de processo para estimar os valores das variáveis quando estas não são transmitidas. Dessa forma, uma diminuição da frequência de transmissão de dados na rede sem fio pode ser obtida e, consequentemente uma redução do consumo energético dos dispositivos sem fio. Resultados de simulações em diferentes condições de operação de um WNCS multivariável de controle de tanques acoplados demonstram que o MPC multi-rate possui características de robustez e é efetivo para aplicações de WNCS, garantindo requisitos de controle e estabilidade mesmo com a diminuição da frequência de transmissão de dados de realimentação na rede sem fio. Adicionalmente, resultados do consumo energético dos dispositivos do WNCS mostraram que o MPC multi-rate proporciona uma economia de energia de até 20% das baterias dos transmissores wireless. Uma análise da eficiência energética do WNCS é apresentada através do estudo dos limites operacionais do controlador MPC multi-rate considerando a relação de compromisso entre o período de amostragem dos dispositivos sem fio e o desempenho de controle do WNCS. / Wireless communication technology has become a fundamental part of the everyday life of process industries, where the use of wireless transmitters for monitoring and control is already a reality. The architecture of Wireless Networked Control Systems (WNCSs) has advantages over point-to-point and wired networks architectures due to the ease of installation, configuration and maintenance. However, the evolution of this technology has introduced new challenges to the implementation of the closed loop control with a wireless instrument as nonlinearities, packet losses and data communication constraints in the wireless networks. Another critical factor related to implementation of WNCSs is the energy source of these transmitters, which have limited lifetime dependent on the amount of access and data transmitted. This work presents the study and the development of a multi-rate predictive controller as an alternative to improve energy efficiency in industrial applications of WNCSs. The proposed strategy does not need to frequently receive updated process variables transmitted by wireless transmitters, because the model predictive controller (MPC) uses the internal submodel of the process variables to estimate the variables values when they are not transmitted. Thus, a decrease in the frequency of data transmission on the wireless network can be obtained and consequently a reduction of energy consumption of wireless devices. Simulation results for different operating conditions of a multivariable WNCS of coupled tanks shows that the multi-rate MPC provides robustness and it is effective for WNCS applications, ensuring control and stability requirements even with the reduction of the transmission frequency of the feedback data in the wireless network. In addition, energy consumption results from the WNCS devices showed that MPC multi-rate provides 20% of energy economy as it is effective in saving the energy expenditure of the wireless transmitter’s battery. An energy efficiency analysis of the WNCS is presented by studying the operating limits of the multi-rate MPC controller considering the compromise relationship between the sampling period of the wireless devices and the control performance of the WNCS.

Esta dissertação de mestrado apresenta um novo esquema de controle de taxa hierárquico – HRC – para o padrão MVC – extensão para vídeos de múltiplas vistas do padrão H.264 – com objetivo de melhorar o aproveitamento da largura de banda oferecida por um canal entregando o vídeo comprimido com a melhor qualidade possível. Este esquema de controle de taxa hierárquico foi concebido para controlar de forma conjunta os níveis de quadro e de unidades básicas (BU). O esquema proposto explora a correlação existente entre as distribuições das taxas de bits em quadros vizinhos para predizer de forma eficiente o comportamento dos futuras bitrates através da aplicação de um controle preditivo baseado em modelos – MPC – que define uma ação de controle apropriada sobre as ações de adaptação do parâmetro de quantização (QP). Para prover um ajuste em granularidade fina, o QP é adicionalmente adaptado internamente para cada quadro por um processo de decisão de Markov (MDP) implementado em nível de BU capaz de considerar mapas com Regiões de Interesse (RoI). Um retorno acoplado aos dois níveis supracitados é realizado para garantir a consistência do sistema. Aprendizagem por Reforço é utilizada para atualizar os parâmetros do Controle Preditivo baseado em Modelos e do processo de decisão de Markov. Resultados experimentais mostram a superioridade da utilização do esquema de controle proposto, comparado às soluções estado-da-arte, tanto em termos de precisão na alocação de bits quanto na otimização da razão taxa-distorção, entregando um vídeo de maior qualidade visual nos níveis de quadros e de BUs. / This master thesis presents a novel Hierarchical Rate Control – HRC – for the Multiview Video Coding standard targeting an increased bandwidth usage and high video quality. The HRC is designed to jointly address the rate control at both framelevel and Basic Unit (BU)-level. This scheme is able to exploit the bitrate distribution correlation with neighboring frames to efficiently predict the future bitrate behavior by employing a Model Predictive Control that defines a proper control action through QP (Quantization Parameter) adaptation. To provide a fine-grained tuning, the QP is further adapted within each frame by a Markov Decision Process implemented at BU-level able to take into consideration a map of the Regions of Interest. A coupled frame/BU-level feedback is performed in order to guarantee the system consistency. A Reinforcement Learning method is responsible for updating the Model Predictive Control and the Markov Decision Process parameters. Experimental results show the superiority of the Hierarchical Rate Control compared to state-of-the-art solutions, in terms of bitrate allocation accuracy and rate-distortion, while delivering smooth video quality at both frame and Basic Unit levels.

Esta dissertação de mestrado apresenta um novo esquema de controle de taxa hierárquico – HRC – para o padrão MVC – extensão para vídeos de múltiplas vistas do padrão H.264 – com objetivo de melhorar o aproveitamento da largura de banda oferecida por um canal entregando o vídeo comprimido com a melhor qualidade possível. Este esquema de controle de taxa hierárquico foi concebido para controlar de forma conjunta os níveis de quadro e de unidades básicas (BU). O esquema proposto explora a correlação existente entre as distribuições das taxas de bits em quadros vizinhos para predizer de forma eficiente o comportamento dos futuras bitrates através da aplicação de um controle preditivo baseado em modelos – MPC – que define uma ação de controle apropriada sobre as ações de adaptação do parâmetro de quantização (QP). Para prover um ajuste em granularidade fina, o QP é adicionalmente adaptado internamente para cada quadro por um processo de decisão de Markov (MDP) implementado em nível de BU capaz de considerar mapas com Regiões de Interesse (RoI). Um retorno acoplado aos dois níveis supracitados é realizado para garantir a consistência do sistema. Aprendizagem por Reforço é utilizada para atualizar os parâmetros do Controle Preditivo baseado em Modelos e do processo de decisão de Markov. Resultados experimentais mostram a superioridade da utilização do esquema de controle proposto, comparado às soluções estado-da-arte, tanto em termos de precisão na alocação de bits quanto na otimização da razão taxa-distorção, entregando um vídeo de maior qualidade visual nos níveis de quadros e de BUs. / This master thesis presents a novel Hierarchical Rate Control – HRC – for the Multiview Video Coding standard targeting an increased bandwidth usage and high video quality. The HRC is designed to jointly address the rate control at both framelevel and Basic Unit (BU)-level. This scheme is able to exploit the bitrate distribution correlation with neighboring frames to efficiently predict the future bitrate behavior by employing a Model Predictive Control that defines a proper control action through QP (Quantization Parameter) adaptation. To provide a fine-grained tuning, the QP is further adapted within each frame by a Markov Decision Process implemented at BU-level able to take into consideration a map of the Regions of Interest. A coupled frame/BU-level feedback is performed in order to guarantee the system consistency. A Reinforcement Learning method is responsible for updating the Model Predictive Control and the Markov Decision Process parameters. Experimental results show the superiority of the Hierarchical Rate Control compared to state-of-the-art solutions, in terms of bitrate allocation accuracy and rate-distortion, while delivering smooth video quality at both frame and Basic Unit levels.

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L'Internet des objets (IoT) devrait interconnecter plus de 50 milliards d’objet d'ici à 2020. Avec l'IoT, une variété d’objets de différentes industries seront interconnectés à travers Internet. Avec un accent sur la gestion et le stockage des ressources énergétique et l'eau. L'IoT permet d’enrichir les services fournis par les distributeurs d’énergie à travers les smart-grid au-delà de la distribution, de l'automatisation et du contrôle. Les systèmes de gestion pour la domotique et les bâtiments intelligents aideront les consommateurs à surveiller et à ajuster leur consommation. Les compteurs intelligents fournissent ainsi un ensemble d’information permettant aux fournisseurs d’énergie de mettre en place des services plus intelligents pour l'ensemble de la chaîne de production d'énergie. L'objectif principal de ce projet de recherche doctorale est de développer des modules de communication très basse consommation. La consommation énergétique étant la plus grande contrainte pour les applications de compteurs intelligents. Les objets connectés alimentés par batterie tels que les capteurs et compteurs de gaz et d'eau sont concernés directement par la consommation en énergie de leur module de communication. Aujourd'hui, la plupart des solutions sans fil embarquées conçues pour capteurs alimentés ne sont pas compatible avec la pile protocolaire IPv6 afin d’économiser la consommation énergétique. Élaborer des technologies sans fil de l'IoT pour atteindre les objectifs de consommation d'énergie va démocratiser l’utilisation de ces technologies et aider les solutions de l’IoT à trouver leur place sur le marché. Ce doctorat débutera par: 1) Un état de l'art permettant d'examiner les solutions actuelles développées pour les réseaux de capteurs et des protocoles conçus pour les appareils alimentés par batterie. 2) Dans un deuxième temps en examinant les solutions Itron pour IPv6 réseau maillé. 3) La troisième phase sera la proposition et la conception d'une solution à faible consommation pour les modules sans fil et l'internet des objets. 4) Et enfin l’expérimentation et la validation des solutions proposées sur des plateformes d’expérimentations / The Internet of Things (IoT) is expected to grow to 50 billion connected devices by 2020. Within the IoT, devices across a variety of industries will be interconnected through the Internet and peer-to-peer connections as well as closed networks like those used in the smart grid infrastructure. With the global focus on energy and water management and conservation, the IoT will extend the connected benefits of the smart grid beyond the distribution, automation and monitoring being done by utility providers. Management systems for in-home and in-building use will help consumers monitor their own usage and adjust behaviors. These systems will eventually regulate automatically by operating during off-peak energy hours and connect to sensors to monitor occupancy, lighting conditions, and more. But it all starts with a smarter and more connected grid. Smart metering provides a base around which utilities can build up smarter advanced services for the whole chain of energy generation, transmission and distribution. The main objective of this doctoral research project is to come up with the IoT communication modules with very low consumption characteristics. The energy consumption is the most challenging issue for smart home and smart metering applications. The battery powered devices such as sensors and gas and water meters are concerned directly with the consumption of their communication module. Today most of the embedded wireless solutions designed for sensors and battery powered devices do not embed IPv6 stack in the communication module to have a basic hardware with low consumption. Elaborating IoT wireless technologies to achieve the tough energy consumption objectives imposed to them will boost up the spread of these technologies and help IoT to find its place in the market fast. This PhD program will start with: First) a state of the art and reviewing the current solutions developed for sensor networks and protocols designed for battery powered devices. Second) it continues by reviewing Itron solutions for IPv6 meshed network. Third) Design of a low consumption solution for IoT wireless modules and) finally test and experimentation on platform