The proposed dissertation research investigates Optimization and Control for Microgrid and Power Electronic Converters. The research has two major parts: i- Microgrid Operation and Control, ii- Power Electronic Converter Control and Optimization. In the first part, three focuses are investigated. First, a completely distributed algorithm is developed for dc optimal power flow problem for power distribution systems as one of the necessary functions considered in unit-commitment problem in day-ahead markets. This method is derived based upon the partial primal-dual representation of the economic dispatch problem, which is finally translated to DC-OPF problem. Second, the optimal interaction between the utility and communities will be studied, due to its improtance in real-time markets. The objective of this section will be to develop an iterative agent-based algorithm for optimal utility-community control. The algorithm will consider the AC power system constraints to maintain power system stability. In this algorithm, a simplified model of microgrid is considered. In the third focus, a comprehensive model of microgrid is taken into account. The optimal operation of the microgrid considering energy storage systems and renewable energy resources is investigated. The interaction of such microgrids with the main grid to define the optimal operation of the entire embedded system is studied through two iterative methods. In the microgrid's internal problem, a moving-horizon algorithm is considered to define the optimal dispatch of all distributed energy resources while considering the time-correlated constraints of energy storage systems. A thorough analysis of the effects of the size of storage systems on energy and reserve market parameters are also performed. In the second part, the focus of research is to develop optimal control strategies for Power Electronic Converters. A Model Predictive Control (MPC) switching method is proposed for Modular Multilevel Converters (MMC). The optimal solution of MPC problem is then represented as an optimization problem. Due to lack of efficient algorithms to seek the optimal solution, a fast algorithm will be proposed in this research. The method proposed reduces the number of possible solutions and computation efforts dramatically.

Orientador: Lee Luan Ling / Dissertação (mestrado) - Universidade Estadual de Campinas, Faculdade de Engenharia Elétrica e de Computação / Made available in DSpace on 2018-08-20T02:24:35Z (GMT). No. of bitstreams: 1 YakovNae_M.pdf: 7990917 bytes, checksum: 122c511d9ba839a2f1464fbe7fca09b4 (MD5) Previous issue date: 2011 / Resumo: Gerência de armazenamento em Redes de Sensores Sem Fio (RSSF) é uma questão muito crítica. Além da RSSFs conter uma vasta quantidade de armazenamento agregada, ela não pode ser usada inteiramente. Portanto, o sistema inteiro falha quando o primeiro sensor tem sua capacidade de armazenamento esgotada, deixando uma grande capacidade de armazenamento inutilizada. Sugere-se que os sensores devem-se ser capazes de detectar as capacidades de armazenamentos inutilizadas, para prolongar as suas funcionalidades. Entretanto, em RSSF de larga escala isso pode ser muito difícil uma vez que os sensores podem não ter conhecimento da existência dos outros. Neste trabalho apresenta-se duas principais contribuições: otimização da capacidade total de armazenamento para RSSF em grande escala e uma nova abordagem de roteamento - Deterministic "Random" Walk (Passeio "Aleatório" Determinístico). Apresenta-se um novo modelo de armazenamento via construção "sob demanda" de Cadeias de Armazenamento Distribuídas ( Distributed Storage Chains (DSC). Estas cadeias representam parcerias entrem os sensores que podem compartilhar suas capacidades de armazenamento. Resultando, os sensores não estão sujeitos às suas limitações de armazenamento, mas para à capacidade total de armazenamento disponível no sistema. Constrói-se estas cadeia via passeio determinístico sobre a topologia sugerida. Todavia, mostra-se que estes passeios apresentam um comportamento aleatório que é muito eficiente em termos de localização de capacidade de armazenamento disponível / Abstract: Storage management of Wireless Sensor Networks (WSN) is a very critical issue in terms of system's lifetime. While WSNs host a vast storage capacity on the aggregate, that capacity cannot be used entirely. Eventually, the entire network may fail when the first sensor has its own storage capacity depleted, leaving behind a large amount of unutilized storage capacity. We suggest that sensors should be able to detect unutilized storage capacity in order to prolong their functionality. However, for large scale WSNs this can be a difficult task, since sensors may not be aware of the existence of others. This work has two main contributions: an optimization of the overall storage capacity for large scale WSNs and a novel routing approach of deterministic "random" walk. We present a new storage model by building "on - demand" Distributed Storage Chains (DSC). These chains represent partnership between sensors that share their storage capacity. As a result, sensors are no longer subjected to their own storage limitations but to the total amount of available storage in the WSN. We construct these chains via deterministic walks over our suggested topology. However, we show that these walks resemble the behavior of random walks and are therefore highly efficient in terms of locating available storage / Mestrado / Telecomunicações e Telemática / Mestre em Engenharia Elétrica

Wireless sensor networks (WSNs) allow us to instrument the physical world in novel ways, providing detailed insight that has not been possible hitherto. Since WSNs provide an interface to the physical world, each sensor node has a location in physical space, thereby enabling us to associate spatial properties with data. Since WSNs can perform periodic sensing tasks, we can also associate temporal markers with data. In the environmental sciences, in particular, WSNs are on the way to becoming an important tool for the modelling of spatially and temporally extended physical phenomena. However, support for high-level and expressive spatial-analytic tasks that can be executed inside WSNs is still incipient. By spatial analysis we mean the ability to explore relationships between spatially-referenced entities (e.g., a vineyard, or a weather front) and to derive representations grounded on such relationships (e.g., the geometrical extent of that part of a vineyard that is covered by mist as the intersection of the geometries that characterize the vineyard and the weather front, respectively). The motivation for this endeavour stems primarily from applications where important decisions hinge on the detection of an event of interest (e.g., the presence, and spatio-temporal progression, of mist over a cultivated field may trigger a particular action) that can be characterized by an event-defining predicate (e.g., humidity greater than 98 and temperature less than 10). At present, in-network spatial analysis in WSN is not catered for by a comprehensive, expressive, well-founded framework. While there has been work on WSN event boundary detection and, in particular, on detecting topological change of WSN-represented spatial entities, this work has tended to be comparatively narrow in scope and aims. The contributions made in this research are constrained to WSNs where every node is tethered to one location in physical space. The research contributions reported here include (a) the definition of a framework for representing geometries; (b) the detailed characterization of an algebra of spatial operators closely inspired, in its scope and structure, by the Schneider-Guting ROSE algebra (i.e., one that is based on a discrete underlying geometry) over the geometries representable by the framework above; (c) distributed in-network algorithms for the operations in the spatial algebra over the representable geometries, thereby enabling (i) new geometries to be derived from induced and asserted ones, and (ii)topological relationships between geometries to be identified; (d) an algorithmic strategy for the evaluation of complex algebraic expressions that is divided into logically-cohesive components; (e) the development of a task processing system that each node is equipped with, thereby with allowing users to evaluate tasks on nodes; and (f) an empirical performance study of the resulting system.

Distributed Approximation is a new and rapidly developing discipline that lies at the crossroads of various well-established areas of Computer Science - Distributed Computing, Approximation Algorithms, Graph Theory and often, Computational Geometry. This thesis focuses on the design and analysis of distributed algorithms to solve optimization problems that usually arise in large-scale, heavily dynamic, resource constrained networks, e.g. wireless ad-hoc and sensor networks, P2P systems, mobile networks etc. These problems can often be abstracted by variations of well-known combinatorial optimization problems, such as topology control, clustering etc. Many of these problems are known to be hard (NP-complete). But we need fast and light-weight distributed algorithms for these problems, that yield near-optimal solutions. The results presented in this thesis can be broadly divided in two parts. The first part contains a set of results that obtain improved solutions to the classic problem of computing a sparse "backbone" for Wireless Sensor Networks (WSNs). In graph-theoretic terms, the goal is to compute a spanning subgraph of the input graph, that is sparse, lightweight and has low stretch. The term "low stretch" indicates that in spite of dropping many edges, the distance between any two nodes in the graph is not increased by much. We model WSNs as geometric graphs - unit ball graphs, quasi-unit ball graphs etc. in Euclidean spaces, as well as in more general metric spaces of low doubling dimension. We identify and exploit a variety of geometric features of those models to obtain our results. In the second part of the thesis we focus on distributed algorithms for clustering problems. We present several distributed approximation algorithms for clustering problems (e.g., minimum dominating set, facility location problems) that improve on best known results so far. The main contribution here is the design of distributed algorithms where the running time is a "tunable" parameter. The advent of distributed systems of unprecedented scale and complexity motivates the question of whether it is possible to design algorithms that can provide non-trivial approximation guarantees even after very few rounds of computation and message exchanges. We call these algorithms "k-round algorithms". We design k-round algorithms for various clustering problems that yield non-trivial approximation factors even if k is a constant. Additionally, if k assumes poly-logarithmic values, our algorithms match or improve on the best-known approximation factors for these problems.

Les automates distribués sont des machines à états finis qui opèrent sur des graphes orientés finis. Fonctionnant comme des algorithmes distribués synchrones, ils utilisent leur graphe d'entrée comme un réseau dans lequel des processeurs identiques communiquent entre eux pendant un certain nombre (éventuellement infini) de rondes synchrones. Pour la variante locale de ces automates, où le nombre de rondes est borné par une constante, Hella et al. (2012, 2015) ont établi une caractérisation logique par des formules de la logique modale de base. Dans le cadre de cette thèse, nous présentons des caractérisations logiques similaires pour deux classes d'automates distribués plus expressives.La première classe étend les automates locaux avec une condition d'acceptation globale et la capacité d'alterner entre des modes de calcul non-déterministes et parallèles. Nous montrons qu'elle est équivalente à la logique monadique du second ordre sur les graphes.En nous restreignant à des transitions non-déterministes ou déterministes, nous obtenons également deux variantes d'automates strictement plus faibles pour lesquelles le problème du vide est décidable.Notre seconde classe adapte la notion standard d'algorithme asynchrone au cadre des automates distribués non-locaux. Les machines résultantes sont prouvées équivalentes à un petit fragment de la logique de point fixe, et plus précisément, à une variante restreinte du μ-calcul modal qui autorise les plus petits points fixes mais interdit les plus grands points fixes. Profitant du lien avec la logique, nous montrons aussi que la puissance expressive de ces automates asynchrones est indépendante du fait que des messages puissent être perdus ou non.Nous étudions ensuite la décidabilité du problème du vide pour plusieurs classes d'automates non-locaux. Nous montrons que le problème est indécidable en général, en simulant une machine de Turing par un automate distribué qui échange les rôles de l'espace et du temps. En revanche, le problème s'avère décidable en LOGSPACE pour une classe d'automates oublieux, où les nœuds voient les messages reçus de leurs voisins, mais ne se souviennent pas de leur propre état. Finalement, à titre de contribution mineure, nous donnons également de nouvelles preuves de séparation pour plusieurs hiérarchies d'alternance de quantificateurs basées sur la logique modale. / Distributed automata are finite-state machines that operate on finitedirected graphs. Acting as synchronous distributed algorithms, they use their input graph as a network in which identical processors communicate for a possibly infinite number of synchronous rounds. For the local variant of those automata, where the number of rounds is bounded by a constant, Hella et al. (2012, 2015) have established a logical characterization in terms of basic modal logic. In this thesis, we provide similar logical characterizations for two more expressive classes of distributed automata.The first class extends local automata with a global acceptance condition and the ability to alternate between non deterministic and parallel computations. We show that it is equivalent to monadic second-order logic on graphs. By restricting transitions to be non deterministic or deterministic, we also obtain two strictly weaker variants for which the emptiness problem is decidable.Our second class transfers the standard notion of asynchronous algorithm to the setting of non local distributed automata. There sulting machines are shown to be equivalent to a small fragment of least fixpoint logic, and more specifically, to a restricted variantof the modal μ -calculus that allows least fixpoints but forbids greatest fixpoints. Exploiting the connection with logic, we additionally prove that the expressive power of those asynchronous automata is independent of whether or not messages can be lost.We then investigate the decidability of the emptiness problem forseveral classes of nonlocal automata. We show that the problem isundecidable in general, by simulating a Turing machine with adistributed automaton that exchanges the roles of space and time. Onthe other hand, the problem is found to be decidable in logspace for a class of forgetful automata, where the nodes see the messages received from their neighbors but cannot remember their own state. As a minor contribution, we also give new proofs of the strictness of several set quantifier alternation hierarchies that are based on modallogic.

We investigate diverse aspects of the performance of wireless networks, including throughput, delay and distributed complexity. <br />One of the main challenges for optimizing them arises from radio interference, an inherent factor in wireless networks.<br />Graph-based interference models represent a large class of interference models widely used for the study of wireless networks,<br />and suffer from the weakness of over-simplifying the interference caused by wireless signals in a local and binary way.<br />A more sophisticated interference model, the physical interference model, based on SINR constraints,<br />is considered more realistic but is more challenging to study (because of its non-linear form and non-local property).<br />In this dissertation, we study the connections between the two types of interference models -- graph-based and physical interference models --<br />and tackle a set of fundamental problems under the physical interference model;<br />previously, some of the problems were still open even under the graph-based interference model, and to those we have provided solutions under both types of interference models.<br /><br />The underlying interference models affect scheduling and power control -- essential building blocks in the operation of wireless networks -- that directly deal with the wireless medium; the physical interference model (compared to graph-based interference model) compounds the problem of efficient scheduling and power control by making it non-local and non-linear.<br />The system performance optimization and tradeoffs with respect to throughput and delay require a ``global\'\' view across<br />transport, network, media access control (MAC), physical layers (referred to as cross-layer optimization)<br />to take advantage of the control planes in different levels of the wireless network protocol stack.<br />This can be achieved by regulating traffic rates, finding traffic flow paths for end-to-end sessions,<br />controlling the access to the wireless medium (or channels),<br />assigning the transmission power, and handling signal reception under interference.<br /><br />The theme of the dissertation is<br />distributed algorithms and optimization of QoS objectives under the physical interference model.<br />We start by developing the first low-complexity distributed scheduling and power control algorithms for maximizing the efficiency ratio for different interference models;<br />we derive end-to-end per-flow delay upper-bounds for our scheduling algorithms and our delay upper-bounds are the first network-size-independent result known for multihop traffic.<br />Based on that, we design the first cross-layer multi-commodity optimization frameworks for delay-constrained throughput maximization by incorporating the routing and traffic control into the problem scope.<br />Scheduling and power control is also inherent to distributed computing of ``global problems\'\', e.g., the maximum independent set problems in terms of transmitting links and local broadcasts respectively, and the minimum spanning tree problems.<br />Under the physical interference model, we provide the first sub-linear time distributed solutions to the maximum independent set problems, and also solve the minimum spanning tree problems efficiently.<br />We develop new techniques and algorithms and exploit the availability of technologies (full-/half-duplex radios, fixed/software-defined power control) to further improve our algorithms.<br />%This fosters a deeper understanding of distributed scheduling from the network computing point of view.<br /><br /><br />We highlight our main technical contributions, which might be of independent interest to the design and analysis of optimization algorithms.<br />Our techniques involve the use of linear and mixed integer programs in delay-constrained throughput maximization. This demonstrates the combined use of different kinds of combinatorial optimization approaches for multi-criteria optimization.<br />We have developed techniques for queueing analysis under general stochastic traffic to analyze network throughput and delay properties.<br />We use randomized algorithms with rigorously analyzed performance guarantees to overcome the distributed nature of wireless data/control communications.<br />We factor in the availability of emerging radio technologies for performance improvements of our algorithms.<br />Some of our algorithmic techniques that would be of broader use in algorithms for the physical interference model include:<br />formal development of the distributed computing model in the SINR model, and reductions between models of different technological capabilities, the redefinition of interference sets in the setting of SINR constraints, and our techniques for distributed computation of rulings (informally, nodes or links which are well-separated covers).<br /> / Ph. D.

Le projet scientifique dans lequel s’inscrit ma thèse a pour objectif l’élaboration d’algorithmes distribués et efficaces pour les réseaux informatiques. Ce projet vise une catégorie particulière des algorithmes distribués, dits auto-stabilisants. Il s’agit d’algorithmes ayant pour propriété de retrouver un comportement correct suite à une panne dans le réseau et ce, sans aucune intervention humaine. Le travail effectué en collaboration avec mes directeurs de thèse s’est concentré, plus précisément, autour des problèmes de couplage, de cliques et des paradigmes de publications-souscriptions dans ce domaine de l’informatique théorique. Dans un premier temps on a traité le problème du couplage maximal dans sa version anonyme, en fournissant un algorithme auto-stabilisant probabiliste et efficace. Ces travaux sont parus dans le journal PPL. De plus, on s’est intéressé au problème du couplage dans sa version maximum identifiée. Son travail améliore le dernier algorithme présent dans la littérature pour l’approximation de ce type de couplage au 2/3 de la solution optimale. Ces travaux sont parus dans une conférence internationale OPODIS. Par ailleurs, j'ai eu l’opportunité de collaborer en Allemagne avec Prof. Volker Turau au sein du groupe de télématique de l’Université technique de Hambourg. Le cadre de cette collaboration a été les algorithmes auto-stabilisants pour les paradigmes de publication-souscription. Cela a abouti à un algorithme efficace pour la version en canal de ce problème, introduisant la notion de raccourci pour le routage de messages dans ces paradigmes. Les résultats ont fait l’objet d’un Brief Announcement et d’un papier, publiés dans des conférences internationales, SSS et NetSyS. J'ai aussi bénéficié d’une collaboration avec Mr. Gerry Siegemund qui a été accueilli au laboratoire d’Informatique de l’École Polytechnique. Il a été question de trouver un algorithme efficace et auto-stabilisant pour la partition d’un réseau en cliques. Cette collaboration a eu pour résultat un algorithme pour le problème améliorant le dernier en date. Ce résultat est en cours de rédaction pour soumission à une conférence internationale. / The main focus of my thesis is the design of an efficient kind of distributed algorithms, known as: Self-stabilizing. These algorithms have the property to recover from faults in the environment they're executed in, and this without any human intervention. Recovering here, means converging toward a pre-defined, correct configuration. In this setting, I was mainly interested by the problems of matching in graphs, clique partitions and publication subscription paradigms. For the maximal version of the matching problem in anonymous graphs, we achieved a more efficient randomized, self-stabilizing algorithm. This work is published in a journal version in PPL. The maximum version of the same problem, but in an identified setting, led to the design of an efficient self-stabilizing algorithm that approximates the optimal solution up to the 2/3. This result was published at OPODIS. During a research visit at TUHH, Hamburg, Germany. Together with Pr. Volker Turau we tackled the problem of self-stabilizing publish/subscribe paradigms. This led to an algorithm introducing the new notion of short-cuts in this type of structures and was published under a brief announcement and a regular paper at SSS and NetSyS. In collaboration with Mr. Siegemund, then a visiting researcher at LIX, École Polytechnique, we worked on an efficient self-stabilizing algorithm for clique partitions. This work is still in progress and in preparation for an eventual publication.

Tesis por compendio / [EN] The long-lasting trend in the field of computation of stress and resource distribution has found its way into computer networks via the concept of peer-to-peer (P2P) connectivity. P2P is a symmetrical model, where each network node is enabled a comparable range of capacities and resources. It stands in a stark contrast to the classical, strongly asymmetrical client-server approach. P2P, originally considered only a complimentary, server-side structure to the straightforward client-server model, has been shown to have the substantial potential on its own, with multiple, widely known benefits: good fault tolerance and recovery, satisfactory scalability and intrinsic load distribution. However, contrary to client-server, P2P networks require sophisticated solutions on all levels, ranging from network organization, to resource location and managing. In this thesis we address one of the key issues of P2P networks: performing efficient resource searches of semantic nature under realistic, dynamic conditions. There have been numerous solutions to this matter, with evolutionary, stigmergy-based, and simple computational foci, but few attempt to resolve the full range of challenges this problem entails. To name a few: real-life P2P networks are rarely static, nodes disconnect, reconnect and change their content. In addition, a trivial incorporation of semantic searches into well-known algorithms causes significant decrease in search efficiency. In our research we build a solution incrementally, starting with the classic Ant Colony System (ACS) within the Ant Colony Optimization metaheuristic (ACO). ACO is an algorithmic framework used for solving combinatorial optimization problems that fits contractually the problem very well, albeit not providing an immediate solution to any of the aforementioned problems. First, we propose an efficient ACS variant in structured (hypercube structured) P2P networks, by enabling a path-post processing algorithm, which called Tabu Route Optimization (TRO). Next, we proceed to resolve the issue of network dynamism with an ACO-compatible information diffusion approach. Consequently, we attempt to incorporate the semantic component of the searches. This initial approximation to the problem was achieved by allowing ACS to differentiate between search types with the pheromone-per-concept idea. We called the outcome of this merger Routing Concept ACS (RC-ACS). RC-ACS is a robust, static multipheromone implementation of ACS. However, we were able to conclude from it that the pheromone-per-concept approach offers only limited scalability and cannot be considered a global solution. Thus, further progress was made in this respect when we introduced to RC-ACS our novel idea: dynamic pheromone creation, which replaces the static one-to-one assignment. We called the resulting algorithm Angry Ant Framework (AAF). In AAF new pheromone levels are created as needed and during the search, rather than prior to it. The final step was to enable AAF, not only to create pheromone levels, but to reassign them to optimize the pheromone usage. The resulting algorithm is called EntropicAAF and it has been evaluated as one of the top-performing algorithms for P2P semantic searches under all conditions. / [ES] La popular tendencia de distribución de carga y recursos en el ámbito de la computación se ha transmitido a las redes computacionales a través del concepto de la conectividad peer-to-peer (P2P). P2P es un modelo simétrico, en el cual a cada nodo de la red se le otorga un rango comparable de capacidades y recursos. Se trata de un fuerte contraste con el clásico y fuertemente asimétrico enfoque cliente-servidor. P2P, originalmente considerado solo como una estructura del lado del servidor complementaria al sencillo modelo cliente-servidor, ha demostrado tener un potencial considerable por sí mismo, con múltiples beneficios ampliamente conocidos: buena tolerancia a fallos y recuperación, escalabilidad satisfactoria y distribución de carga intrínseca. Sin embargo, al contrario que el modelo cliente-servidor, las redes P2P requieren de soluciones sofisticadas a todos los niveles, desde la organización de la red hasta la gestión y localización de recursos. Esta tesis aborda uno de los problemas principales de las redes P2P: la búsqueda eficiente de recursos de naturaleza semántica bajo condiciones dinámicas y realistas. Ha habido numerosas soluciones a este problema basadas en enfoques evolucionarios, estigmérgicos y simples, pero pocas han tratado de resolver el abanico completo de desafíos. En primer lugar, las redes P2P reales son raramente estáticas: los nodos se desconectan, reconectan y cambian de contenido. Además, la incorporación trivial de búsquedas semánticas en algoritmos conocidos causa un decremento significativo de la eficiencia de la búsqueda. En esta investigación se ha construido una solución de manera incremental, comenzando por el clásico Ant Colony System (ACS) basado en la metaheurística de Ant Colony Optimization (ACO). ACO es un framework algorítmico usado para búsquedas en grafos que encaja perfectamente con las condiciones del problema, aunque no provee una solución inmediata a las cuestiones mencionadas anteriormente. En primer lugar, se propone una variante eficiente de ACS para redes P2P estructuradas (con estructura de hipercubo) permitiendo el postprocesamiento de las rutas, al que hemos denominado Tabu Route Optimization (TRO). A continuación, se ha tratado de resolver el problema del dinamismo de la red mediante la difusión de la información a través de una estrategia compatible con ACO. En consecuencia, se ha tratado de incorporar el componente semántico de las búsquedas. Esta aproximación inicial al problema ha sido lograda permitiendo al ACS diferenciar entre tipos de búsquedas através de la idea de pheromone-per-concept. El resultado de esta fusión se ha denominado Routing Concept ACS (RC-ACS). RC-ACS es una implementación multiferomona estática y robusta de ACS. Sin embargo, a partir de esta implementación se ha podido concluir que el enfoque pheromone-per-concept ofrece solo escalabilidad limitada y que no puede ser considerado una solución global. Por lo tanto, para lograr una mejora a este respecto, se ha introducido al RC-ACS una novedosa idea: la creación dinámica de feromonas, que reemplaza la asignación estática uno a uno. En el algoritmo resultante, al que hemos denominado Angry Ant Framework (AAF), los nuevos niveles de feromona se crean conforme se necesitan y durante la búsqueda, en lugar de crearse antes de la misma. La mejora final se ha obtenido al permitir al AAF no solo crear niveles de feromona, sino también reasignarlos para optimizar el uso de la misma. El algoritmo resultante se denomina EntropicAAF y ha sido evaluado como uno de los algoritmos más exitosos para las búsquedas semánticas P2P bajo todas las condiciones. / [CA] La popular tendència de distribuir càrrega i recursos en el camp de la computació s'ha estès cap a les xarxes d'ordinadors a través del concepte de connexions d'igual a igual (de l'anglès, peer to peer o P2P). P2P és un model simètric on cada node de la xarxa disposa del mateix nombre de capacitats i recursos. P2P, considerat originàriament només una estructura situada al servidor complementària al model client-servidor simple, ha provat tindre el suficient potencial per ella mateixa, amb múltiples beneficis ben coneguts: una bona tolerància a errades i recuperació, una satisfactòria escalabilitat i una intrínseca distribució de càrrega. No obstant, contràriament al client-servidor, les xarxes P2P requereixen solucions sofisticades a tots els nivells, que varien des de l'organització de la xarxa a la localització de recursos i la seua gestió. En aquesta tesi s'adreça un dels problemes clau de les xarxes P2P: ser capaç de realitzar eficientment cerques de recursos de naturalesa semàntica sota condicions realistes i dinàmiques. Existeixen nombroses solucions a aquest tema basades en la computació simple, evolutiva i també basades en l'estimèrgia (de l'anglès, stigmergy), però pocs esforços s'han realitzat per intentar resoldre l'ampli conjunt de reptes existent. En primer lloc, les xarxes P2P reals són rarament estàtiques: els nodes es connecten, desconnecten i canvien els seus continguts. A més a més, la incorporació trivial de cerques semàntiques als algorismes existents causa una disminució significant de l'eficiència de la cerca. En aquesta recerca s'ha construït una solució incremental, començant pel sistema clàssic de colònia de formigues (de l'anglés, Ant Colony System o ACS) dins de la metaheurística d'optimització de colònies de formigues (de l'anglès, Ant Colony Optimization o ACO). ACO és un entorn algorísmic utilitzat per cercar en grafs i que aborda el problema de forma satisfactòria, tot i que no proveeix d'una solució immediata a cap dels problemes anteriorment mencionats. Primer, s'ha proposat una variant eficient d'ACS en xarxes P2P estructurades (en forma d'hipercub) a través d'un algorisme de processament post-camí el qual s'ha anomenat en anglès Tabu Route Optimization (TRO). A continuació, s'ha procedit a resoldre el problema del dinamisme de les xarxes amb un enfocament de difusió d'informació compatible amb ACO. Com a conseqüència, s'ha intentat incorporar la component semàntica de les cerques. Aquest enfocament inicial al problema s'ha realitzat permetent a ACS diferenciar entre tipus de cerques amb la idea de ''feromona per concepte'', i s'ha anomenat a aquest producte Routing Concept ACS o RC-ACS. RC-ACS és una implementació multi-feromona robusta i estàtica d'ACS. No obstant, s'ha pogut concloure que l'enfocament de feromona per concepte ofereix només una escalabilitat limitada i no pot ser considerada una solució global. En aquest respecte s'ha realitzat progrés posteriorment introduint una nova idea a RC-ACS: la creació dinàmica de feromones, la qual reemplaça a l'assignació un a un de les mateixes. A l'algorisme resultant se l'ha anomenat en anglès Angry Ant Framework (AAF). En AAF es creen nous nivells de feromones a mesura que es necessiten durant la cerca, i no abans d'aquesta. El progrés final s'ha aconseguit quan s'ha permès a AAF, no sols crear nivells de feromones, sinó reassignar-los per optimitzar la utilització de feromones. L'algorisme resultant s'ha anomenat EntropicAAF i ha sigut avaluat com un dels algorismes per a cerques semàntiques P2P amb millors prestacions. / Krynicki, KK. (2016). Ant Colony Algorithms for the Resolution of Semantic Searches in P2P Networks [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/61293 / TESIS / Premios Extraordinarios de tesis doctorales / Compendio

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