Management solutions for current and future Infrastructure-as-a-Service (IaaS) Data Centers (DCs) face complex challenges. First, DCs are now very large infrastructures holding hundreds of thousands if not millions of servers and applications. Second, DCs are highly heterogeneous. DC infrastructures consist of servers and network devices with different capabilities from various vendors and different generations. Cloud applications are owned by different tenants and have different characteristics and requirements. Third, most DC elements are highly dynamic. Applications can change over time. During their lifetime, their logical architectures evolve and change according to workload and resource requirements. Failures and bursty resource demand can lead to unstable states affecting a large number of services. Global and centralized approaches limit scalability and are not suitable for large dynamic DC environments with multiple tenants with different application requirements. We propose a novel fully distributed and dynamic management paradigm for highly diverse and volatile DC environments. We develop LAMA, a novel framework for managing large scale cloud infrastructures based on a multi-agent system (MAS). Provider agents collaborate to advertise and manage available resources, while app agents provide integrated and customized application management. Distributing management tasks allows LAMA to scale naturally. Integrated approach improves its efficiency. The proximity to the application and knowledge of the DC environment allow agents to quickly react to changes in performance and to pre-plan for potential failures. We implement and deploy LAMA in a testbed server cluster. We demonstrate how LAMA improves scalability of management tasks such as provisioning and monitoring. We evaluate LAMA in light of state-of-the-art open source frameworks. LAMA enables customized dynamic management strategies to multi-tier applications. These strategies can be configured to respond to failures and workload changes within the limits of the desired SLA for each application.

A qualidade do serviço oferecido por Provedores do Serviço de Internet (Internet Service Provider - ISPs) depende diretamente da quantidade de recursos disponíveis naquele momento. Nas últimas décadas, essa qualidade tem sido afetada por frequentes e intensos ataques que consomem tais recursos, como é o caso dos ataques de Negação de Serviço Distribuídos (Distributed Denial of Service - DDoS). Com o objetivo de tornar a rede dos ISPs mais resiliente aos diferentes tipos de ataques DDoS, foram desenvolvidas técnicas contra tais ataques ao longo dos últimos anos. Com o objetivo de contribuir com a melhoria de tais mecanismos, esta dissertação apresenta um método autônomo reativo para detecção e mitigação de ataques DDoS, utilizando um sistema multiagentes (SMA), em redes de ISPs. A propriedade principal do método proposto é identificar padrões de tráfego característicos de um ataque, como um grande fluxo de pacotes direcionados para um serviço ou equipamento, dentro da rede do ISP. Com os agentes posicionados nas prováveis vítimas e nos pontos da rede com maior fluxo de pacotes, o processo de mitigação inicia-se automaticamente após uma quantidade de pacotes, excedente ao tráfego padrão, passar por qualquer um dos nós monitorados. Como o tráfego entrante na rede do ISP é dinâmico, seja ele legítimo ou malicioso, a utilização de agentes tende a facilitar o processo de definição da rota de ataque, conforme mostram os resultados experimentais obtido com o sistema proposto. / The quality of service offered by the Internet Service Provider (ISP) depends directly on the amount of resources available at that time. In recent decades, this quality has been affected by the frequent and intense attacks that consume these resources, such as the Distributed Denial of Service (DDoS) attacks. In order to make the ISPs network more resilient to different types of DDoS attacks, techniques have been developed against such attacks over the past few years. Aiming to contribute to the improvement of such mechanisms, this dissertation presents a reactive autonomous method for detecting and mitigating DDoS attacks using a Multi-Agent system (MAS), in networks of ISPs. The main property of the proposed method is to identify characteristic traffic patterns of an attack, such as a large stream of packets directed to a service or equipment within the ISP network. With agents positioned on likely victims and at points of the network with the highest packet stream, the mitigation process starts automatically after a number of packets exceeding the traffic pattern, go through any of the monitored nodes. Since the incoming traffic on the network of any ISP is dynamic, whether legitimate or malicious, the using of agents tends to facilitate the process of defining the route of attack, as shown by the experimental results obtained with the proposed system.

Esta dissertação propõe uma Ontologia Funcional de Reputação para agentes. Tal ontologia representa uma parte do conhecimento científico sobre reputação provido tanto pelas Ciências Humanas quanto pelos trabalhos em Inteligência Artificial. Seu objetivo é oferecer uma perspectiva funcional para a representação e análise da reputação como mecanismo de controle social em sociedades de agentes, de forma a sustentar a implementação de modelos de reputação para agentes. A Ontologia Funcional de Reputação foi construída a partir das categorias de conhecimento da Ontologia Funcional do Direito, proposta por Valente (1995), e utiliza a categorização de conceitos definida para o mundo jurídico para a representação do mundo social. A ontologia foi codificada em OWL DL, uma linguagem formal baseada em lógica descritiva. Uma vez construída a ontologia, os conceitos utilizados por diversos modelos e sistemas de reputação foram utilizados na sua avaliação. A utilização de um motor de inferência permitiu comparar estes conceitos, representados por meio de classes OWL, com as classes da ontologia. Tal comparação permite avaliar, de modo preliminar, a adequação do uso da Ontologia Funcional de Reputação como uma possível interlingua entre diversos agentes heterogêneos, cada qual utilizando um modelo de reputação diferente, que necessitam interoperar. / This work presents a Functional Ontology of Reputation for agents. This ontology represents the broad knowledge about reputation produced in some areas of interest such as Social Sciences and Artificial Intelligence. Its goal is to provide a functional perspective both to represent and analyze reputation as a social control mechanism for agent’s societies, in order to support the implementation of reputation model for agents. The Functional Ontology of Reputation employs the primitive categories of knowledge used in the Functional Ontology of Law proposed by Valente (1995). The idea is that the concepts of the legal world can be used to model the social world, through the extension of the concept of legal rule to social norm and the internalization of social control mechanisms in the agent's mind, so far externalized in legal institutions. The Functional Ontology of Reputation contains five main categories that have been borrowed from or inspired by the Functional Ontology of Law: Reputative Knowledge, Responsibility Knowledge, Normative Knowledge, World Knowledge and Common Sense Knowledge.As in the Functional Ontology of Law, the distinction among the categories of the reputation ontology are accomplished according to a functional perspective, in which each component of the reputation system, embedded in the social system, exists to perform a specific function in the effort to achieve social objectives, such as trust, reciprocity and social cooperation. The Functional Ontology of Reputation was implemented in OWL, a description logic language. This ontology was evaluated by using several concepts related to reputation, included in different reputation models and reputation systems. These concepts were defined as OWL classes and a reasoner was used in order to produce the comparison between these concepts and the ontology classes. This comparison allows evaluating, in a preliminary way, the Functional Ontology of Reputation utilization as a possible interlingua between several heterogeneous agents that need to interoperate, despite the utilization of different reputation model.

In direct reference to the saying “time is money”, nowadays scenario simulations play a key role in the tasks people perform. Optimizing the time length of tasks and synchronizing them properly is essential to increased profits in any line of business. In this thesis the Bergkvist-Insjön sawmill yard process will be computer simulated. As the number of trucks arriving at the sawmill is unknown, the unexpected arrival of trucks would produce a high pressure on internal resources and handling operations. The aim of this paper is to optimize the usage of the resources in the Bergkvist-Insjön sawmill, by running three different scenarios built based on the real system simulation. Scenario number three, in which a log stacker only has the tasks to unload the trucks and supply the measurement station, has been found most efficient. In the simulation of this scenario, the number of logs processed by the sawmill is the highest one. Also, the time spent by the log stackers between their tasks is the shortest one from all scenarios. The results of this thesis revealed that the most efficient improvement of the sawmill yard would be gained by a different tasks’ priority for the operating log stackers.

A qualidade do serviço oferecido por Provedores do Serviço de Internet (Internet Service Provider - ISPs) depende diretamente da quantidade de recursos disponíveis naquele momento. Nas últimas décadas, essa qualidade tem sido afetada por frequentes e intensos ataques que consomem tais recursos, como é o caso dos ataques de Negação de Serviço Distribuídos (Distributed Denial of Service - DDoS). Com o objetivo de tornar a rede dos ISPs mais resiliente aos diferentes tipos de ataques DDoS, foram desenvolvidas técnicas contra tais ataques ao longo dos últimos anos. Com o objetivo de contribuir com a melhoria de tais mecanismos, esta dissertação apresenta um método autônomo reativo para detecção e mitigação de ataques DDoS, utilizando um sistema multiagentes (SMA), em redes de ISPs. A propriedade principal do método proposto é identificar padrões de tráfego característicos de um ataque, como um grande fluxo de pacotes direcionados para um serviço ou equipamento, dentro da rede do ISP. Com os agentes posicionados nas prováveis vítimas e nos pontos da rede com maior fluxo de pacotes, o processo de mitigação inicia-se automaticamente após uma quantidade de pacotes, excedente ao tráfego padrão, passar por qualquer um dos nós monitorados. Como o tráfego entrante na rede do ISP é dinâmico, seja ele legítimo ou malicioso, a utilização de agentes tende a facilitar o processo de definição da rota de ataque, conforme mostram os resultados experimentais obtido com o sistema proposto. / The quality of service offered by the Internet Service Provider (ISP) depends directly on the amount of resources available at that time. In recent decades, this quality has been affected by the frequent and intense attacks that consume these resources, such as the Distributed Denial of Service (DDoS) attacks. In order to make the ISPs network more resilient to different types of DDoS attacks, techniques have been developed against such attacks over the past few years. Aiming to contribute to the improvement of such mechanisms, this dissertation presents a reactive autonomous method for detecting and mitigating DDoS attacks using a Multi-Agent system (MAS), in networks of ISPs. The main property of the proposed method is to identify characteristic traffic patterns of an attack, such as a large stream of packets directed to a service or equipment within the ISP network. With agents positioned on likely victims and at points of the network with the highest packet stream, the mitigation process starts automatically after a number of packets exceeding the traffic pattern, go through any of the monitored nodes. Since the incoming traffic on the network of any ISP is dynamic, whether legitimate or malicious, the using of agents tends to facilitate the process of defining the route of attack, as shown by the experimental results obtained with the proposed system.

Le Conseil Général de la Gironde (CG33) est une collectivité territoriale qui met en oeuvre les politiques décidées par des élus. L’une de ses missions fondamentales est l’induction de comportements auprès des citoyens, des acteurs économiques et institutionnels. Citons par exemple la concrétisation, par l’intermédiaire de la réalisation de projets, des politiques publiques autour des thématiques du développement Durable (DD). Un constat issu des retours d’expérience s’impose : les projets mis en oeuvre au CG 33 sont de plus en plus complexes. Ils requièrent la collaboration de nombreux acteurs publics et privés qui se connaissent mal. Les démarches territoriales de DD nécessitent l’articulation de compétences spécifiques et interdépendantes, qui n’existent pas chez un acteur unique. Ces constats sont généralisables, quel que soit le secteur d’activité professionnelle. La connaissance, l’identification et le partage optimal de compétences est au coeur même de la réussite de projets. La problématique consiste à répondre aux attentes de tout maître d’oeuvre qui doit être capable de définir un projet, d’identifier les compétences qui le composent, les acteurs capables d’exercer ces compétences, puis finalement d’évaluer à postériori la réussite globale du projet. Définir la liste des compétences n’est pas toujours aisé puisqu’elles évoluent au fil du temps. Elles peuvent, par exemple, se transformer suite à l’arrivée d’évolutions techniques. Elles peuvent également disparaitre si elles sont remplacées ou bien finalement non utilisées. Un système optimal se doit donc d’être dynamique lors de la constitution des projets au fil du temps, dans le but de coller au plus prêt de la réalité du contexte dans lequel le système est utilisé. Nous voyons bien ici que la Compétence(et non l’acteur) est l’élément fondamental du système.Une réponse dite « classique » pourrait consister à réaliser simplement une base de données où les compétences et acteurs seraient des objets statiques. Cette solution ne répondant pas à notre souhait de dynamisme. Nous proposons plutôt un système informatique collaboratif, accessible en ligne, dans lequel nous définissions des « agents compétence » (AC), dynamiques et apprenants, qui évoluent au sein d’une architecture de type multi-agents. Chaque AC y est unique, bien qu’il puisse être incarné sur le terrain par plusieurs acteurs humains. Il possède une « vie propre », des moyens d'actions multiples et multi-localisés (réparti sur plusieurs acteurs physiques). Tout AC dispose de mécanismes de perception de son environnement, de communication avec les autres ACs. Il utilise de ressources (telles que les acteurs humains) et vise à réaliser 4buts principaux :1. Constituer sa propre définition (liste des compétences élémentaires) 2. Restituer une liste d’acteurs humains capables de le concrétiser sur le terrain3. Etablir des relations avec d’autres ACs afin d’optimiser la constitution des projets4. Se porter spontanément candidat à une participation à de nouveaux projets. Nos ACs ont également un « cycle de vie » décliné en 3 « âges » (enfance, adolescence et maturité). Chacun d’eux correspond à un niveau d’autonomie particulier. Notre SMA est de type «évènementiel ». Les agents y évoluent grâce aux interactions avec les194 utilisateurs humains du système. Un « modèle comportemental » dédié et évolutif est proposé dans le but d’optimiser leur dynamisme et de stimuler leur apprentissage. / In France, the “Conseil Général de la Gironde” is a local authority that promotes various sustainable development policies and practices. One of its missions is to coordinate and stimulate public and private partnerships in the framework of green building projects.Whatever the sector of professional activities and the thematic addressed, the concrete projects’ feedbacks show all the complexity to succeed in managing efficiently the collaboration of involved actors. Indeed, each of them has only a partial knowledge ofthe others’ skills. To answer to the problematic, and in order to improve the management of the projects, we propose an online collaborative tool that allows actors to share skills. According to the “Multi-Agent” theory, "skill agents" have been defined.The key idea is to consider that a skill is an agent of the system, and the actors are only its resources.Skill agents are dynamic and autonomous, have learning abilities, and have their ownlife cycle. They pursue four main goals: building their own definition, identifying actorswho can concretize them across projects, setting up links with other skill agents, and beeing candidates to new projects. Skill agents interact with human actors to stimulate their cooperation.This work shows that our model is appropriate for complex collaborative projects,giving results in various areas. For example, a case study based on the selection of players to form a rugby team has been given.

Le travail présenté dans cette thèse définit une nouvelle approche pour la modélisation et la conceptualisation des processus métiers dans les entreprises afin de construire des outils logiciels d'assistance intelligents qui prennent en charge ces processus. L'approche proposée définit une ontologie dédiée à l'étude des organisations, nommée K-CRIO. Elle est décrite à l'aide du langage de représentation des connaissances OWL. Afin d'illustrer nos travaux, un système d'assistance a été implanté sur la base des résultats issus de la modélisation et de la conceptualisation d'un processus métier spécifique avec l'ontologie K-CRIO. Ce système prend la forme d'une application Web qui intègre et exploite pleinement les avantages des systèmes multiagents. L'ontologie K-CRIO est une ontologie dédiée à l'étude des organisations et à l'analyse organisationnelle des processus métiers qu'elles mettent en oeuvre. Plus précisément, elle est utilisée pour comprendre, analyser et raisonner sur ces organisations. Les organisations visées sont celles composées d'acteurs humains impliqués tout au long de la conception de produits et, pour ce faire, organisés selon un processus métier. L'éventail de ce type d'organisations est assez large. Nous avons donc limité notre étude aux organisations qui produisent des logiciels comme objectif final du processus. Dans ce contexte, l'ontologie K-CRIO peut être utilisée pour modéliser la structure organisationnelle du processus et les activités qui en résultent. Cette ontologie peut ensuite être exploitée afin de concevoir des outils d'assistance à la mise en oeuvre des processus ciblés au sein des organisations décrites. Plus précisément, l'ontologie fournit des moyens de raisonnement, d'annotation des ressources, et de suivi des processus de conception, permettant des recherches et de proposer pro-activement des conseils et des contenus appropriés. Afin d'illustrer l'utilisation de K-CRIO, nous appliquons K-CRIO sur deux processus différents: le modèle en cascade et la méthodologie Scrum. Ces exemples sont des processus de développement de logiciels classiques. En outre, pour le processus Scrum, qui est un processus agile de développement de logiciel, largement utilisé dans les entreprises de logiciels, nous avons conçu et développé un outil d'assistance intelligent. Cet outil contribue principalement à aider les Scrum Masters en leur fournissant des indicateurs pour les assister dans leurs prises de décisions ainsi que par la constitution d'une base de connaissances sur les activités / The work presented in this PhD thesis defines a new approach for the modeling and the conceptualization of enterprise business processes in the perspective of building intelligent assistance software tools to support these processes. The proposed approach defines an organizational ontology, named K-CRIO. Its description is based on the Ontology Web Language. To illustrate our work, an intelligent assistance system has been designed and implemented according to the result from the modeling and conceptualization of a specific business process with the K-CRIO Ontology. It is a web-based application that integrates and takes full advantage of multi-agent systems.The K-CRIO Ontology is an Ontology dedicated to the study of organizations and the analysis of business processes adopting an organizational point of view. Specifically, it is used to understand, analyze and reason about organizations and the processes they implement. The targeted organizations are those composed of entities involved throughout products' design and, to do so, following a defined business process. The range of this type of organizations is quite wide. We have thus limited our study to organizations that produce software as the final process goal, specifically IT enterprises delivering software products or services. In this context, the K-CRIO ontology could be used to model structure of the considered organizations and model human activities appearing in their business processes. This ontology could be used to support process assistance within the described organizations. More specifically, the ontology could provide means for reasoning, annotating resources, monitoring design processes, enabling searches and pro-actively proposing tips and proper content. In order to illustrate the usage of K-CRIO, we apply K-CRIO on two different processes: the Waterfall Model and the Scrum methodology. These examples are both classical software-development processes. Moreover, for Scrum, the famous agile software-development process widely used in software enterprises, we have designed and developed an intelligent assistance tool. This tool mainly helps Scrum Masters to make decision by monitoring Scrum project teams' activities within their various projects and collecting knowledge about these activities.

對於現有文獻中討論的預測市場模型，嘗試加入風險與聲譽變數，觀察與分析其成效，並參考文獻中的代理人系統實驗方法，對論文中相關部分進行修正、設計並模擬之預測市場模型。 / In this research, we proposed two variables that could be incorporated with prediction markets: Reputation and Risk. Instead of attracting new players, The reputation system could stop losing bankrupted player, Player willing to help bankrupted player will gain reputation, and bankrupted player will lose reputation. Previous works suggest longshot bias is related to the risk-neutrality of players. Our approach is to experiment dierent risk distribution. We observe the impact of these variables in an agent-based model of prediction markets. We use zero-intelligence agents, where human qualities such as maximizing prot, learning or obeserving are missing. We further discuss the result, and the impact of risk and reputation.

All-electric ship power systems have limited generation capacity and finite rotating inertia compared with large power systems. Moreover, all-electric ship power systems include large portions of nonlinear loads and dynamic loads relative to the total power capacity, which may significantly reduce the stability margin. Pulse loads and other high-energy weapon loads in the system draw a large amount of power intermittently, which may cause significant frequency and voltage oscillations in the system. Thus, an effective real-time load management technique is needed to dynamically balance the load and generation to operate the system normally. Multi-agent systems, inspired by biological phenomena, aim to cooperatively achieve system objectives that are difficult to reach by a single agent or centralized controller. Since power systems include various electrical components with different dynamical systems, conventional homogeneous multi-agent system cooperative controllers have difficulties solving the real-time load management problem with heterogeneous agents. In this dissertation, a novel heterogeneous multi-agent system cooperative control methodology is presented based on artificial potential functions and reduced-order agent models to cooperatively achieve real-time load management for all-electric ship power systems. The technique integrates high-order system dynamics and various kinds of operational constraints into the multi-agent system, which improves the accuracy of the cooperative controller. The multi-agent system includes a MVAC multiagent system and a DC zone multi-agent, which are coordinated by an AC-DC communication agent. The developed multi-agent system framework and the notional all-electric ship power system model were simulated in PSCAD software. Case studies and performance analysis of the MVAC multi-agent system and the DC zone multi-agent system were performed. The simulation results indicated that propulsion loads and pulse loads can be successfully coordinated to reduce the impact of pulse loads on the power quality of all-electric ship power systems. Further, the switch status or power set-point of loads in DC zones can be optimally determined to dynamically balance the generation and load while satisfying the operational constraints of the system and considering load priorities. The method has great potential to be extended to other isolated power systems, such as microgrids.

Energy is consumed every day at home as we perform simple tasks, such as watching television, washing dishes and heating/cooling home spaces during season of extreme weather conditions, using appliances, or turning on lights. Most often, the energy resources used in residential systems are obtained from natural gas, coal and oil. Moreover, climate change has increased awareness of a need for expendable, energy resources. As a result, carbon dioxide emissions are increasing and creating a negative effect on our environment and on our health. In fact, growing energy demands and limited natural resource might have negative impacts on our future. Therefore, saving energy is becoming an important issue in our society and it is receiving more attention from the research community. This thesis introduces a intelligent energy controller algorithm based on software agent approach that reduce the energy consumption at home for both heating and cooling spaces by considering the user’s occupancy, outdoor temperature and user’s preferences as input to the system. Thus the proposed approach takes into consideration the occupant’s preferred temperature, the occupied and unoccupied spaces, as well as the time spent in each area of the home. A Java based simulator has been implemented to simulate the algorithm for saving energy in heating and cooling systems. The results from the simulator are compared to the results of using HOT2000, which is Canada’s leading residential energy analysis and rating software developed by CanmetENERGY’s Housing, Buildings, Communities and Simulation (HBCS) group. We have calculated how much energy a home modelled will use under emulated conditions. The results showed that the implementation of the proposed energy controller algorithm can save up to 50% in energy consumption in homes dedicated to heating and cooling systems compared to the results obtained by using HOT2000.