A significant progress in the evolution of the computer systems and their interconnection over the past 70 years has allowed replacing the frequently used centralized architectures with the highly distributed ones, formed by independent entities fulfilling specific functionalities as one user-intransparent unit. This has resulted in an intense scientic interest in distributed algorithms and their frequent implementation into real systems. Especially, distributed algorithms for multi-sensor data fusion, ensuring an enhanced QoS of executed applications, find a wide usage. This doctoral thesis addresses an optimization and an analysis of the distributed systems, namely the distributed consensus-based algorithms for an aggregate function estimation (primarily, my attention is focused on a mean estimation). The first section is concerned with a theoretical background of the distributed systems, their evolution, their architectures, and a comparison with the centralized systems (i.e. their advantages/disadvantages). The second chapter deals with multi-sensor data fusion, its application, the classification of the distributed estimation techniques, their mathematical modeling, and frequently quoted algorithms for distributed averaging (e.g. protocol Push-Sum, Metropolis-Hastings weights, Best Constant weights etc.). The practical part is focused on mechanisms for an optimization of the distributed systems, the proposal of novel algorithms and complements for the distributed systems, their analysis, and comparative studies in terms of such as the convergence rate, the estimation precision, the robustness, the applicability to real systems etc.

Consensus occurs within a multi-agent system when every agent is in agreement about the value of some particular state. For example, the color of an LED, the position or magnitude of a vector, a rendezvous location, the most recent state of data within a database, or the identity of a leader are all states that agents might need to agree on in order to execute their tasking. The task of the decentralized consensus problem for multi-agent systems is to design an algorithm that enables agents to communicate and exchange information such that, in finite time, agents are able to form a consensus without the use of a centralized control mechanism. The primary goal of this research is to introduce and provide supporting evidence for Stochastic Local Observation/Gossip (SLOG) algorithms as a new class of solutions to the decentralized consensus problem for multi-agent systems that lack a centralized controller, with the additional constraints that agents act asynchronously, information is discrete, and all consensus options are equally preferable to all agents. Examples of where these constraints might apply include the spread of social norms and conventions in artificial populations, rendezvous among a set of specific locations, and task assignment. This goal is achieved through a combination of theory and experimentation. Information propagation process and an information propagation algorithm are derived by unifying the general structure of multiple existing solutions to the decentralized consensus problem. They are then used to define two classes of algorithms that spread information across a network and solve the decentralized consensus problem: buffered gossip algorithms and local observation algorithms. Buffered gossip algorithms generalize the behavior of many push-based solutions to the decentralized consensus problem. Local observation algorithms generalize the behavior of many pull-based solutions to the decentralized consensus problem. In the language of object oriented design, buffered gossip algorithms and local observation algorithms are abstract classes; information propagation processes are interfaces. SLOG algorithms combine the transmission mechanisms of buffered gossip algorithms and local observation algorithms into a single "hybrid" algorithm that is able to push and pull information within the local neighborhood. A common mathematical framework is constructed and used to determine the conditions under which each of these algorithms are guaranteed to produce a consensus, and thus solve the decentralized consensus problem. Finally, a series of simulation experiments are conducted to study the performance of SLOG algorithms. These experiments compare the average speed of consensus formation between buffered gossip algorithms, local observation algorithms, and SLOG algorithms over four distinct network topologies. Beyond the introduction of the SLOG algorithm, this research also contributes to the existing literature on the decentralized consensus problem by: specifying a theoretical framework that can be used to explore the consensus behavior of push-based and pull-based information propagation algorithms; using this framework to define buffered gossip algorithms and local observation algorithms as generalizations for existing solutions to the decentralized consensus problem; highlighting the similarities between consensus algorithms within control theory and opinion dynamics within computational sociology, and showing how these research areas can be successfully combined to create new and powerful algorithms; and providing an empirical comparison between multiple information propagation algorithms.

Due to the absence of appropriate security mechanisms, even the latest version of Board Gateway Protocol (BGP) is still highly vulnerable to malicious routing hijacking. The original problem is that BGP allows router to accept any BGP update message without any extra validation process. Resource Public Key Infrastructure (RPKI) issues a series of digital signature certificates to provide binding relationship between the IP prefix in the route advertisement and the Autonomous System (AS) number on the propagation path to protect BGP routing. However, RPKI is a centralized architecture in which Certification Authority (CA) can launch power abuses attacks, such as unilaterally certificate revocation or publication repository tampering. In this thesis, we propose a blockchain-based BGP security infrastructure, named BGPcredit. The BGPcredit system synchronizes RPKI certificates by consensus process. It can maintain identical RPKI certificates repository across the whole system through blockchain, providing necessary security protection for BGP routing. In order to provide such features, we customize a proper consensus algorithm for BGPcredit which a reasonable credence management mechanism, credit computing function, block forger election process, Verifiable Random Function (VRF) are introduced. Also, the blockchain is customized to meet the system requirements. Moreover, BGPcredit advocates to make fully use of the trust of certification authorities to build a partially decentralized system. Some trusted nodes with higher authority are set to enhance the system’s security and robustness. Finally, I implement the BGPcredit prototype and conduct some validation experiments to test its performance. / På grund av avsaknaden av lämpliga säkerhetsmekanismer är även den senaste versionen av BGP fortfarande mycket sårbar för skadlig routerkappning. Det ursprungliga problemet är att BGP tillåter routern att acceptera alla BGP uppdateringsmeddelande utan någon extra valideringsprocess. RPKI utfärdar en serie digitala signaturcertifikat för att ge bindande relation mellan IP-adressprefixet i ruttannonsen och AS-numret på spridningsvägen för att skydda BGP-routningssäkerheten. Men RPKI är för centraliserad och CA kan starta strömmissbruk, till exempel ensidigt återkallande av certifikat och skadlig modifiering av publikationsregistret. I detta projekt föreslår vi en blockkedjebaserad BGP-säkerhetsinfrastruktur, kallad BGPcredit. Detta system synkroniserar RPKI-certifikat genom konsensusprocessen och kan upprätthålla identiska RPKI-certifikat arkiv över hela systemet genom blockchain, vilket ger nödvändigt säkerhetsskydd för BGP-routing. För att tillhandahålla sådana funktioner skräddarsyr vi en lämplig konsensusalgoritm baserad på nodkredit för BGPcredit som inkluderar en rimlig kredithanteringsmekanism, kreditberäkningsfunktion, blockförfalskningsprocess, VRF, etc. Dessutom har vissa anpassade ändringar i blockchain gjorts för att uppfylla systemkraven. Dessutom förespråkar BGPcredit att fullt ut utnyttja certifieringsmyndigheternas förtroende för att bygga upp ett delvis decentraliserat system. Vissa tillförlitliga noder med högre auktoritet är inställda för att förbättra systemets säkerhet och robusthet. Slutligen implementerar vi BGPcredit prototypen och genomför några valideringsexperiment. Resultaten visar att BGPcredit kan fungera bra och är kompatibel med BGP routing nätverk.

Esta tese de doutorado trata de algoritmos de detecção cooperativa aplicados ao problema de sensoriamento espectral em sistemas de rádios cognitivos. O problema de detecção cooperativa é abordado sob dois paradigmas distintos: detecção centralizada e distribuída. No primeiro caso, considera-se que o sistema conta com um centro de fusão responsável pela tomada de decisão no processo de detecção. Já no segundo caso, considera-se que os rádios cognitivos da rede trocam informações entre si e as decisões são tomadas localmente. No que concerne ao sensoriamento espectral centralizado, são estudados os casos em que os rádios cognitivos enviam apenas um bit de decisão para o centro de fusão (decisão do tipo hard) e também o caso em que o detector envia a própria estatística de teste ao centro de fusão (decisão do tipo soft). No âmbito de sensoriamento espectral cooperativo com detecção distribuída, são tratados três cenários diferentes. No primeiro, considera-se o caso em que os rádios cognitivos têm conhecimento a priori do sinal enviado pelo usuário primário do sistema e do canal entre eles e o usuário primário. No segundo caso, há conhecimento apenas do sinal enviado pelo usuário primário. Já no terceiro, os rádios cognitivos não dispõem de qualquer informação a priori do sinal enviado pelo usuário primário. Além do problema de detecção distribuída, a tese também apresenta um capítulo dedicado ao problema de estimação, diretamente associado ao de detecção. Esse último problema é abordado utilizando algoritmos derivados da teoria clássica de filtragem adaptativa. / This doctorate thesis deals with cooperative detection algorithms applied to the spectral sensing problem. The cooperative detection problem is approached under two different paradigms: centralized and distributed detection. In the first case, is considered that a fusion center responsible for detection decision is presented in the system. On the other hand, in the second case, is considered that the cognitive radios in the network exchange information among them. Concerning the centralized spectrum sensing system, the case in which the cognitive radios send only one decision bit (hard decision) to the fusion center and the case in which the detector send the statistic test (soft decision) are considered. Regarding the spectrum sensing system with distributed detection, the work analysis three different scenarios. In the first one, where the cognitive radios explore an a priori knowledge of the primary user signal and the channel between the primary user and the cognitive radio. In the second one, the cognitive radios use an a priori knowledge of only the primary user signal. And, in the las scenario, there is no a priori knowledge about the primary user signal. Besides the distributed detection problem, the thesis also presents a chapter dedicated to the estimation problem, which is directed related to the detection problem. This last issue is approached using adaptive algorithms derived from the classic adaptive filtering theory.

Esta tese de doutorado trata de algoritmos de detecção cooperativa aplicados ao problema de sensoriamento espectral em sistemas de rádios cognitivos. O problema de detecção cooperativa é abordado sob dois paradigmas distintos: detecção centralizada e distribuída. No primeiro caso, considera-se que o sistema conta com um centro de fusão responsável pela tomada de decisão no processo de detecção. Já no segundo caso, considera-se que os rádios cognitivos da rede trocam informações entre si e as decisões são tomadas localmente. No que concerne ao sensoriamento espectral centralizado, são estudados os casos em que os rádios cognitivos enviam apenas um bit de decisão para o centro de fusão (decisão do tipo hard) e também o caso em que o detector envia a própria estatística de teste ao centro de fusão (decisão do tipo soft). No âmbito de sensoriamento espectral cooperativo com detecção distribuída, são tratados três cenários diferentes. No primeiro, considera-se o caso em que os rádios cognitivos têm conhecimento a priori do sinal enviado pelo usuário primário do sistema e do canal entre eles e o usuário primário. No segundo caso, há conhecimento apenas do sinal enviado pelo usuário primário. Já no terceiro, os rádios cognitivos não dispõem de qualquer informação a priori do sinal enviado pelo usuário primário. Além do problema de detecção distribuída, a tese também apresenta um capítulo dedicado ao problema de estimação, diretamente associado ao de detecção. Esse último problema é abordado utilizando algoritmos derivados da teoria clássica de filtragem adaptativa. / This doctorate thesis deals with cooperative detection algorithms applied to the spectral sensing problem. The cooperative detection problem is approached under two different paradigms: centralized and distributed detection. In the first case, is considered that a fusion center responsible for detection decision is presented in the system. On the other hand, in the second case, is considered that the cognitive radios in the network exchange information among them. Concerning the centralized spectrum sensing system, the case in which the cognitive radios send only one decision bit (hard decision) to the fusion center and the case in which the detector send the statistic test (soft decision) are considered. Regarding the spectrum sensing system with distributed detection, the work analysis three different scenarios. In the first one, where the cognitive radios explore an a priori knowledge of the primary user signal and the channel between the primary user and the cognitive radio. In the second one, the cognitive radios use an a priori knowledge of only the primary user signal. And, in the las scenario, there is no a priori knowledge about the primary user signal. Besides the distributed detection problem, the thesis also presents a chapter dedicated to the estimation problem, which is directed related to the detection problem. This last issue is approached using adaptive algorithms derived from the classic adaptive filtering theory.

Ces dernières années, l’émergence des nouvelles technologies tels que la miniaturisation des composants, les dispositifs de communication sans fils, l’augmentation de la taille de stockage et les capacités de calcul, a permis la conception de systèmes multi-agents coopératifs de plus en plus complexes. L’un des plus grands axes de recherche dans cette thématique concerne la commande en formation de flottes de véhicules autonomes. Un grand nombre d’applications et de missions, civiles et militaires, telles que l’exploration, la surveillance, et la maintenance, ont alors été développées et réalisées dans des milieux variés (terre, air, eau). Durant l’exécution de ces tâches, les véhicules doivent interagir avec leur environnement et entre eux pour se coordonner. Les outils de communication disponibles disposent souvent d’une portée limitée. La préservation de la connexion au sein du groupe devient alors un des objectifs à satisfaire pour que la tâche puisse être accomplie avec succès. Une des possibilités pour garantir cette contrainte est le déplacement en formation permettant de préserver les distances et la structure géométrique du groupe. Il est toutefois nécessaire de disposer d’outils et de méthodes d’analyse et de commande de ces types de systèmes afin d’exploiter au maximum leurs potentiels. Cette thèse s’inscrit dans cette direction de recherche en présentant une synthèse et une analyse des systèmes dynamiques multi-agents et plus particulièrement la commande en formation de véhicules autonomes. Les lois de commande développées dans la littérature pour la commande en formation permettent d’accomplir un grand nombre de missions avec un niveau de performance élevé. Toutefois, si un défaut/défaillant apparaît dans la formation, ces lois de commandes peuvent s’avérer très limitées, engendrant un comportement instable du système. Le développement de commandes tolérantes aux défauts devient alors primordial pour maintenir les performances de commande en présence de défauts. Cette problématique sera traitée dans ce mémoire de thèse et concernera le développement et la conception de commandes en formation tolérantes au défaut dévolu à une flotte de véhicules autonomes suivant différente configuration/structuration / In recent years, the emergence of new technologies such as miniaturization of components, wireless communication devices, increased storage size and computing capabilities have allowed the design of increasingly complex cooperative multi-agent systems. One of the main research axes in this topic concerns the formation control of fleets of autonomous vehicles. Many applications and missions, civilian and military, such as exploration, surveillance, and maintenance, were developed and carried out in various environments. During the execution of these tasks, the vehicles must interact with their environment and among themselves to coordinate. The available communication tools are often limited in scope. The preservation of the connection within the group then becomes one of the objectives to be satisfied in order to carry out the task successfully. One of the possibilities to guarantee this constraint is the training displacement, which makes it possible to preserve the distances and the geometrical structure of the group. However, it is necessary to have tools and methods for analyzing and controlling these types of systems in order to make the most of their potential. This thesis is part of this research direction by presenting a synthesis and analysis of multi-agent dynamical systems and more particularly the formation control of autonomous vehicles. The control laws developed in the literature for formation control allow to carry out a large number of missions with a high level of performance. However, if a fault/failure occurs in the training, these control laws can be very limited, resulting in unstable system behavior. The development of fault tolerant controls becomes paramount to maintaining control performance in the presence of faults. This problem will be dealt with in more detail in this thesis and will concern the development and design of Fault tolerant controls devolved to a fleet of autonomous vehicles according to different configuration/structuring