<p>Network and system management has always been of concern for telecommunication and computer system operators. The need for standardization was recognised already 20 years ago, hence several standards for network management exist today. However, the ever-increasing number of units connected to networks and the ever-increasing number of services being provided results in significant increased complexity of average network environments. This challenges current management systems. In addition to the general increase in complexity the trend among network owners and operators of merging several single service networks into larger, heterogeneous and complex full service networks challenges current management systems even further. The full service networks will require management systems more powerful than what is possible to realize basing systems purely on todays management standards. This thesis presents a distributed stochastic optimization algorithm which enables implementations of highly robust and efficient management tools. These tools may be integrated into management systems and potentially make the systems more powerful and better prepared for management of full service networks.</p><p>Emergent behavior is common in nature and easily observable in colonies of social insects and animals. Even an old oak tree can be viewed as an emergent system with its collection of interacting cells. Characteristic for any emergent system is how the overall behavior of the system emerge from many relatively simple, restricted behaviors interacting, e.g. a thousand ants building a trail, a flock of birds flying south or millions of cells making a tree grow. No centralized control exist, i.e. no single unit is in charge making global decisions. Despite distributed control, high work redundancy and stochastic behavior components, emergent systems tend to be very efficient problem solvers. In fact emergent systems tend to be both efficient, adaptive and robust which are three properties indeed desirable for a network management system. The algorithm presented in this thesis relates to a class of emergent behavior based systems known as swarm intelligence systems, i.e. the algorithm is potentially efficient, adaptive and robust.</p><p>On the contrary to other related swarm intelligence algorithms, the algorithm presented has a thorough formal foundation. This enables a better understanding of the algorithm’s potentials and limitations, and hence enables better adaptation of the algorithm to new problem areas without loss of efficiency, adaptability or robustness. The formal foundations are based on work by Reuven Rubinstein on cross entropy driven optimization. The transition from Ruinstein’s centralized and synchronous algorithm to a distributed and asynchronous algorithm is described, and the distributed algorithm’s ability to solve complex problems (NP-complete) efficiently is demonstrated.</p><p>Four examples of how the distributed algorithm may be applied in a network management context are presented. A system for finding near optimal patterns of primary/backup paths together with a system for finding cyclic protection paths in mesh networks demonstrate the algorithm’s ability to act as a tool helping management system to ensure quality of service. The algorithm’s potential as a management policy implementation mechanism is also demonstrated. The algorithm’s adaptability is shown to enable resolution of policy conflicts in a soft manner causing as little loss as possible. Finally, the algorithm’s ability to find near optimal paths (i.e. sequences) of resources in networks of large scale is demonstrated.</p>

Network and system management has always been of concern for telecommunication and computer system operators. The need for standardization was recognised already 20 years ago, hence several standards for network management exist today. However, the ever-increasing number of units connected to networks and the ever-increasing number of services being provided results in significant increased complexity of average network environments. This challenges current management systems. In addition to the general increase in complexity the trend among network owners and operators of merging several single service networks into larger, heterogeneous and complex full service networks challenges current management systems even further. The full service networks will require management systems more powerful than what is possible to realize basing systems purely on todays management standards. This thesis presents a distributed stochastic optimization algorithm which enables implementations of highly robust and efficient management tools. These tools may be integrated into management systems and potentially make the systems more powerful and better prepared for management of full service networks. Emergent behavior is common in nature and easily observable in colonies of social insects and animals. Even an old oak tree can be viewed as an emergent system with its collection of interacting cells. Characteristic for any emergent system is how the overall behavior of the system emerge from many relatively simple, restricted behaviors interacting, e.g. a thousand ants building a trail, a flock of birds flying south or millions of cells making a tree grow. No centralized control exist, i.e. no single unit is in charge making global decisions. Despite distributed control, high work redundancy and stochastic behavior components, emergent systems tend to be very efficient problem solvers. In fact emergent systems tend to be both efficient, adaptive and robust which are three properties indeed desirable for a network management system. The algorithm presented in this thesis relates to a class of emergent behavior based systems known as swarm intelligence systems, i.e. the algorithm is potentially efficient, adaptive and robust. On the contrary to other related swarm intelligence algorithms, the algorithm presented has a thorough formal foundation. This enables a better understanding of the algorithm’s potentials and limitations, and hence enables better adaptation of the algorithm to new problem areas without loss of efficiency, adaptability or robustness. The formal foundations are based on work by Reuven Rubinstein on cross entropy driven optimization. The transition from Ruinstein’s centralized and synchronous algorithm to a distributed and asynchronous algorithm is described, and the distributed algorithm’s ability to solve complex problems (NP-complete) efficiently is demonstrated. Four examples of how the distributed algorithm may be applied in a network management context are presented. A system for finding near optimal patterns of primary/backup paths together with a system for finding cyclic protection paths in mesh networks demonstrate the algorithm’s ability to act as a tool helping management system to ensure quality of service. The algorithm’s potential as a management policy implementation mechanism is also demonstrated. The algorithm’s adaptability is shown to enable resolution of policy conflicts in a soft manner causing as little loss as possible. Finally, the algorithm’s ability to find near optimal paths (i.e. sequences) of resources in networks of large scale is demonstrated.

Economic dispatch is an important optimization challenge in power systems. It helps to find the optimal output power of a number of generating units that satisfy the system load demand at the cheapest cost, considering equality and inequality constraints. Many nature inspired algorithms have been broadly applied to tackle it such as particle swarm optimization. In this dissertation, two improved particle swarm optimization techniques are proposed to solve economic dispatch problems. The first is a hybrid technique with Bat algorithm. Particle swarm optimization as the main optimizer integrates bat algorithm in order to boost its velocity and to adjust the improved solution. The second proposed approach is based on Cuckoo operations. Cuckoo search algorithm is a robust and powerful technique to solve optimization problems. The study investigates the effect of levy flight and random search operation in Cuckoo search in order to ameliorate the performance of the particle swarm optimization algorithm. The two improved particle swarm algorithms are firstly tested on a range of 10 standard benchmark functions and then applied to five different cases of economic dispatch problems comprising 6, 13, 15, 40 and 140 generating units. / Electrical and Mining Engineering / M. Tech. (Electrical Engineering)

We look at robotic systems made of separate discrete components that, by self-assembling, can organize into physical structures of growing size. We review 22 such systems, exhibiting components ranging from passive mechanical parts to mobile robots. We present a taxonomy of the systems, and discuss their design and function. We then focus on a particular system, the swarm-bot. In swarm-bot, the components that assemble are self-propelled modules that are fully autonomous in power, perception, computation, and action. We examine the additional capabilities and functions self-assembly can offer an autonomous group of modules for the accomplishment of a concrete task: the transport of an object. The design of controllers is accomplished in simulation using techniques from biologically-inspired computing. We show that self-assembly can offer adaptive value to groups that compete in an artificial evolution based on their fitness in task performance. Moreover, we investigate mechanisms that facilitate the design of self-assembling systems. The controllers are transferred to the physical swarm-bot system, and the capabilities of self-assembly and object transport are extensively evaluated in a range of different environments. Additionally, the controller for self-assembly is transferred and evaluated on a different robotic system, a super-mechano colony. Given the breadth and quality of the results obtained, we can say that the swarm-bot qualifies as the current state of the art in self-assembling robots. Our work supplies some initial evidence (in form of simulations and experiments with the swarm-bot) that self-assembly can offer robotic systems additional capabilities and functions useful for the accomplishment of concrete tasks.

Orientador: Jefferson Nascimento de Oliveira / Resumo: Os direitos da natureza são indispensáveis para a harmonia nos espaços de atuação e desenvolvimento da vida, onde o uso e a ocupação do solo impactam diretamente na disponibilidade e qualidade de recursos fundamentais como a água e outros bens comuns. Com a observação de iniciativas transnacionais, governamentais, laboratórios de ciência aberta, empresas e ONGs, esta pesquisa exploratória consolida cenários sobre intensos fluxos de multidões à deriva de projeções e sobre a capacidade adaptativa de aglomerados no Antropoceno. São elementos onde a Internet e os paradigmas do serviço total incitam plataformas digitais para novos produtos e serviços, adequadas à realidade dos jogos sociais contemporâneos. Com bases e referenciais em governança eletrônica para as águas, os resultados das explorações resultam na descoberta das organizações associativas cibernéticas (cyorgs) e as características fundamentais dos Escritórios da Resiliência Hídrica. Amparados por espaços antropológicos, de interação e implementações estratégicas de inovação em sustentabilidade, os produtos constroém a plataforma ÁguasML - Bem Comum em Mídia Livre, implementada digitalmente com código aberto via portais de notícias, ambientes de aprendizagem, automatizações e aplicativos para coleta e distribuição de dados. Apontam também alguns dos componentes das plataformas hidrotecnológicas nos Escritórios da Resiliência Hídrica, assim como os conteúdos, as experiências e as características de tecnologias resilient... (Resumo completo, clicar acesso eletrônico abaixo) / Abstract: The rights of nature are indispensable for harmony in the spaces of participation and development of life, where the use and occupation of the lands directly affect the availability and quality of water and other commons. Observing transnational initiatives, governments, open science laboratories, corporations and NGOs, this exploratory research consolidates scenarios of intense flows of crowds drifting from projections and adaptive capacity in the Anthropocene. They are elements in which the internet and the paradigms of the total service incite digital platforms for new products and services, adapted to the mechanized reality of contemporary social games. With these baselines and benchmarks in electronic governance for water, the results of explorations are the discovery of cybernetic associative organizations (cyorgs) and the fundamental characteristics of Water Resilience Office´s. Based on anthropological spaces, spaces of interaction and strategic implementations of innovation in water sustainability, the work build the ÁguasML - Commons in Open Media platform, digitally implemented with open source through news portals, e-learning environments, automations and applications for collection and data distribution. They also show some of the components of hydrotechnology platforms at the offices for water resilience, as well as the contents, experiences and characteristics of resilient technologies in situations of water scarcity and vulnerability of rights. This office gen... (Complete abstract click electronic access below) / Mestre

Uma das premissas fundamentais em redes fotônicas baseadas na tecnologia de multiplexação por comprimento de onda (WDM) é o controle dos caminhos ópticos. Um caminho óptico, ou caminho de luz, é uma conexão puramente óptica estabelecida entre dois nós da rede, que pode atravessar diversos nós intermediários. Para dar suporte eficiente à demanda exigida de uma rede WDM sobre a qual executam aplicações de alto desempenho, os caminhos ópticos devem ser estabelecidos e encerrados dinamicamente, de tal forma que as rotas e os comprimentos de onda escolhidos minimizem a probabilidade de ocorrência de bloqueios de conexão por falta de recursos disponíveis. O elemento central de uma rede WDM é o sistema que controla os comutadores ópticos, determina as rotas, aloca os comprimentos de onda, e estabelece, mantém e encerra as conexões ópticas entre os nós da rede. O objetivo deste trabalho é apresentar estratégias de roteamento e de atribuição de comprimentos de onda para redes fotônicas usando heurísticas baseadas em inteligência de enxame. Os resultados demonstram que as estratégias desenvolvidas apresentam baixa probabilidade de bloqueio de requisições e buscam, sempre que possível, os caminhos de menor custo. As estratégias desenvolvidas levam em conta o dinamismo da rede, sendo as decisões de caminho baseadas em dados atualizados em cada nó da rede em tempo real, sem a necessidade do conhecimento global do estado da rede em cada nó. / A fundamental aspect of photonic networks based on wavelength division multiplexing (WDM) technology is the control of optical paths. An optical path, or lightpath, is a purely optical connection established between two network nodes, which can pass through several intermediate nodes. To efficiently support the demands required from a WDM network that runs high performance applications, the optical paths should be established and finished dynamically, in such a way that the selected routes and wavelengths tend to minimize the blocking probability due to the lack of available resources. The central element of a WDM network is the system that controls the optical switches, determines routes, allocates the wavelengths, and establishes, maintains and finishes connections between optical network nodes. The purpose is to present strategies for routing and wavelength assignment over photonic networks using heuristics based on swarm intelligence. Results show that the developed strategies exhibit low blocking probability of requests and find the paths of minimum cost whenever possible. The strategies developed take into account the dynamics of the network, and decisions are based on updated data at each network node in real time without the need of a complete knowledge of network state at each node.

A visão de muitas pessoas sobre uma colônia de formigas, em geral, é de que estes pequenos e inofensivos insetos somente se movem aleatoriamente para coletar alimento e conservá-los em seus ninhos. Um olhar destreinado não conseguiria notar o nível de complexidade e organização que é requerido por uma colônia de formigas para sua sobrevivência. Uma formiga simples é parte de um grande grupo que coopera entre si para criar um superorganismo. Sem uma autoridade central ou indivíduos com habilidade de um pensamento cognitivo complexo, a colônia se auto-organiza, e, de fato, ajusta seus recursos de uma maneira muito eficiente. Essa dissertação investiga o papel da comunicação indireta nas tarefas de exploração e forrageamento, e como isso afeta as decisões de um agente simples e traz um comportamento emergente útil à toda colônia. Por fim, este trabalho implementa uma plataforma de simulação multi-agente inspirado em formigas / Most people\'s view of an ant colony and ants in general is that they simply pose harmless little insects that move randomly and gather food in their underground nests. The untrained eye would have never guessed the level of complexity and organisation that is required in order for an ant colony to survive. The simple ant is a part of a huge group, which cooperate one superorganism. Without any central authority or the ability of complex cognitive thought from the individuals, the colony seems to self organise and in fact adjust its resources in a quite efficient way. This dissertation investigates the role of indirect communication in the exploration and forage task and how it affects the decisions of the single agent and brings an emergent behaviour that is useful to all the colony. Finally this work implements an ant inspired multi-agent simulation plataform

University of Macau / Faculty of Science and Technology. / Department of Computer and Information Science

Uma das premissas fundamentais em redes fotônicas baseadas na tecnologia de multiplexação por comprimento de onda (WDM) é o controle dos caminhos ópticos. Um caminho óptico, ou caminho de luz, é uma conexão puramente óptica estabelecida entre dois nós da rede, que pode atravessar diversos nós intermediários. Para dar suporte eficiente à demanda exigida de uma rede WDM sobre a qual executam aplicações de alto desempenho, os caminhos ópticos devem ser estabelecidos e encerrados dinamicamente, de tal forma que as rotas e os comprimentos de onda escolhidos minimizem a probabilidade de ocorrência de bloqueios de conexão por falta de recursos disponíveis. O elemento central de uma rede WDM é o sistema que controla os comutadores ópticos, determina as rotas, aloca os comprimentos de onda, e estabelece, mantém e encerra as conexões ópticas entre os nós da rede. O objetivo deste trabalho é apresentar estratégias de roteamento e de atribuição de comprimentos de onda para redes fotônicas usando heurísticas baseadas em inteligência de enxame. Os resultados demonstram que as estratégias desenvolvidas apresentam baixa probabilidade de bloqueio de requisições e buscam, sempre que possível, os caminhos de menor custo. As estratégias desenvolvidas levam em conta o dinamismo da rede, sendo as decisões de caminho baseadas em dados atualizados em cada nó da rede em tempo real, sem a necessidade do conhecimento global do estado da rede em cada nó. / A fundamental aspect of photonic networks based on wavelength division multiplexing (WDM) technology is the control of optical paths. An optical path, or lightpath, is a purely optical connection established between two network nodes, which can pass through several intermediate nodes. To efficiently support the demands required from a WDM network that runs high performance applications, the optical paths should be established and finished dynamically, in such a way that the selected routes and wavelengths tend to minimize the blocking probability due to the lack of available resources. The central element of a WDM network is the system that controls the optical switches, determines routes, allocates the wavelengths, and establishes, maintains and finishes connections between optical network nodes. The purpose is to present strategies for routing and wavelength assignment over photonic networks using heuristics based on swarm intelligence. Results show that the developed strategies exhibit low blocking probability of requests and find the paths of minimum cost whenever possible. The strategies developed take into account the dynamics of the network, and decisions are based on updated data at each network node in real time without the need of a complete knowledge of network state at each node.

Dans cette thèse, nous nous sommes intéressés à l'impact de la quantité et de la qualité de l'information échangée entre individus d'un groupe sur leurs performances collectives dans deux types de tâches bien spécifiques. Dans une première série d'expériences, les sujets devaient estimer des quantités séquentiellement, et pouvaient réviser leurs estimations après avoir reçu comme information sociale l'estimation moyenne d'autres sujets. Nous contrôlions cette information sociale à l'aide de participants virtuels (dont nous contrôlions le nombre) donnant une information (dont nous contrôlions la valeur), à l'insu des sujets. Nous avons montré que lorsque les sujets ont peu de connaissance préalable sur une quantité à estimer, (les logarithmes de) leurs estimations suivent une distribution de Laplace. La médiane étant un bon estimateur du centre d'une distribution de Laplace, nous avons défini la performance collective comme la proximité de la médiane (du logarithme) des estimations à la vraie valeur. Nous avons trouvé qu'après influence sociale, et lorsque les agents virtuels fournissent une information correcte, la performance collective augmente avec la quantité d'information fournie (fraction d'agents virtuels). Nous avons aussi analysé la sensibilité à l'influence sociale des sujets, et trouvé que celle-ci augmente avec la distance entre l'estimation personnelle et l'information sociale. Ces analyses ont permis de définir 5 traits de comportement : garder son opinion, adopter celle des autres, faire un compromis, amplifier l'information sociale ou au contraire la contredire. Nos résultats montrent que les sujets qui adoptent l'opinion des autres sont ceux qui améliorent le mieux leur performance, car ils sont capables de bénéficier de l'information apportée par les agents virtuels. Nous avons ensuite utilisé ces analyses pour construire et calibrer un modèle d'estimation collective, qui reproduit quantitativement les résultats expérimentaux et prédit qu'une quantité limitée d'information incorrecte peut contrebalancer un biais cognitif des sujets consistant à sous-estimer les quantités, et ainsi améliorer la performance collective. D'autres expériences ont permis de valider cette prédiction. Dans une seconde série d'expériences, des groupes de 22 piétons devaient se séparer en clusters de la même "couleur", sans indice visuel (les couleurs étaient inconnues), après une courte période de marche aléatoire. Pour les aider à accomplir leur tâche, nous avons utilisé un système de filtrage de l'information disponible (analogue à un dispositif sensoriel tel que la rétine), prenant en entrée l'ensemble des positions et couleurs des individus, et retournant un signal sonore aux sujets (émit par des tags attachés à leurs épaules) lorsque la majorité de leurs k plus proches voisins était de l'autre couleur que la leur. La règle consistait à s'arrêter de marcher lorsque le signal stoppait. / In this thesis, we were interested in the impact of the quantity and quality of information ex- changed between individuals in a group on their collective performance in two very specific types of tasks. In a first series of experiments, subjects had to estimate quantities sequentially, and could revise their estimates after receiving the average estimate of other subjects as social information. We controlled this social information through virtual participants (which number we controlled) giving information (which value we controlled), unknowingly to the subjects. We showed that when subjects have little prior knowledge about a quantity to estimate, (the loga- rithms of) their estimates follow a Laplace distribution. Since the median is a good estimator of the center of a Laplace distribution, we defined collective performance as the proximity of the median (log) estimate to the true value. We found that after social influence, and when the information provided by the virtual agents is correct, the collective performance increases with the amount of information provided (fraction of virtual agents). We also analysed subjects' sensitivity to social influence, and found that it increases with the distance between personal estimate and social information. These analyses made it possible to define five behavioral traits: to keep one's opinion, to adopt that of others, to compromise, to amplify social information or to contradict it. Our results showed that the subjects who adopt the opinion of others are the ones who best improve their performance because they are able to benefit from the infor- mation provided by the virtual agents. We then used these analyses to construct and calibrate a model of collective estimation, which quantitatively reproduced the experimental results and predicted that a limited amount of incorrect information can counterbalance a cognitive bias that makes subjects underestimate quantities, and thus improve collective performance. Further experiments have validated this prediction. In a second series of experiments, groups of 22 pedestrians had to segregate into clusters of the same "color", without visual cue (the colors were unknown), after a short period of random walk. To help them accomplish their task, we used an information filtering system (analogous to a sensory device such as the retina), taking all the positions and colors of individuals in input, and returning an acoustic signal to the subjects (emitted by tags attached to their shoulders) when the majority of their k nearest neighbors was of a different color from theirs.