The LHCb online system relies on a large and heterogeneous IT infrastructure made from thousands of servers on which many different applications are running. They run a great variety of tasks : critical ones such as data taking and secondary ones like web servers. The administration of such a system and making sure it is working properly represents a very important workload for the small expert-operator team. Research has been performed to try to automatize (some) system administration tasks, starting in 2001 when IBM defined the so-called "self objectives" supposed to lead to "autonomic computing". In this context, we present a framework that makes use of artificial intelligence and machine learning to monitor and diagnose at a low level and in a non intrusive way Linux-based systems and their interaction with software. Moreover, the shared experience approach we use, coupled with an "object oriented paradigm" architecture increases a lot our learning speed, and highlight relations between problems.

Dans le contexte de l’informatique pervasive et de l’internet des objets, les systèmes sonthétérogènes, distribués et adaptatifs (p. ex., systèmes de gestion des transports, bâtimentsintelligents). La conception et le déploiement de ces systèmes sont rendus difficiles par leurnature hétérogène et distribuée mais aussi le risque de décisions d’adaptation conflictuelleset d’inconsistances à l’exécution. Les inconsistances sont causées par des pannes matériellesou des erreurs de communication. Elles surviennent lorsque des actions correspondant auxdécisions d’adaptation sont supposées être effectuées alors qu’elles ne le sont pas.Cette thèse propose un support intergiciel, appelé SICODAF, pour la conception et ledéploiement de systèmes adaptatifs fiables. SICODAF combine une fiabilité comportementale(absence de décisions conflictuelles) au moyen de systèmes de transitions et une fiabilitéd’exécution (absence d’inconsistances) à l’aide d’un intergiciel transactionnel. SICODAF estbasé sur le calcul autonomique. Il permet de concevoir et de déployer un système adaptatifsous la forme d’une boucle autonomique qui est constituée d’une couche d’abstraction, d’unmécanisme d’exécution transactionnelle et d’un contrôleur. SICODAF supporte trois typesde contrôleurs (basés sur des règles, sur la théorie du contrôle continu ou discret). Il permetégalement la reconfiguration d’une boucle, afin de gérer les changements d’objectifs quisurviennent dans le système considéré, et l’intégration d’un système de détection de pannesmatérielles. Enfin, SICODAF permet la conception de boucles multiples pour des systèmesqui sont constitués de nombreuses entités ou qui requièrent des contrôleurs de types différents.Ces boucles peuvent être combinées en parallèle, coordonnées ou hiérarchiques.SICODAF a été mis en oeuvre à l’aide de l’intergiciel transactionnel LINC, de l’environnementd’abstraction PUTUTU et du langage Heptagon/BZR qui est basé sur des systèmesde transitions. SICODAF a été également évalué à l’aide de trois études de cas. / In the context of pervasive computing and internet of things, systems are heterogeneous,distributed and adaptive (e.g., transport management systems, building automation). Thedesign and the deployment of these systems are made difficult by their heterogeneous anddistributed nature but also by the risk of conflicting adaptation decisions and inconsistenciesat runtime. Inconsistencies are caused by hardware failures or communication errors. Theyoccur when actions corresponding to the adaptation decisions are assumed to be performedbut are not done.This thesis proposes a middleware support, called SICODAF, for the design and thedeployment of reliable adaptive systems. SICODAF combines a behavioral reliability (absenceof conflicting decisions) by means of transitions systems and an execution reliability(absence of inconsistencies) through a transactional middleware. SICODAF is based on autonomiccomputing. It allows to design and deploy an adaptive system in the form of anautonomic loop which consists of an abstraction layer, a transactional execution mechanismand a controller. SICODAF supports three types of controllers (based on rules, on continuousor discrete control theory). SICODAF also allows for loop reconfiguration, to dealwith changing objectives in the considered system, and the integration of a hardware failuredetection system. Finally, SICODAF allows for the design of multiple loops for systems thatconsist of a high number of entities or that require controllers of different types. These loopscan be combined in parallel, coordinated or hierarchical.SICODAF was implemented using the transactional middleware LINC, the abstractionenvironment PUTUTU and the language Heptagon/BZR that is based on transitionssystems. SICODAF was also evaluated using three case studies.

L'objectif de cette thèse est d'offrir une solution de bout en bout permettant de décrire et de déployer de façon fiable une application distribuée dans un environnement virtualisé. Ceci passe par la définition d'un formalisme permettant de décrirer une application ainsi que son environnement d'exécution, puis de fournir les outils capable d'interpéter ce formalisme pour déployer (installer, instancier et configurer) l'application sur une plate-forme de type cloud computing. / Cloud computing aims to cut down on the outlay and operational expenses involved in setting up and running applications. To do this, an application is split into a set of virtualized hardware and software resources. This virtualized application can be autonomously managed, making it responsive to the dynamic changes affecting its running environment. This is referred to as Application Life-cycle Management (ALM). In cloud computing, ALM is a growing but immature market, with many offers claiming to significantly improve productivity. However, all these solutions are faced with a major restriction: the duality between the level of autonomy they offer and the type of applications they can handle. To address this, this thesis focuses on managing the initial deployment of an application to demonstrate that the duality is artificial. The main contributions of this work are presented in a platform named VAMP (Virtual Applications Management Platform). VAMP can deploy any legacy application distributed in the cloud, in an autonomous, generic and reliable way. It consists of: • a component-based model to describe the elements making up an application and their projection on the running infrastructure, as well as the dependencies binding them in the applicative architecture; • an asynchronous, distributed and reliable protocol for self-configuration and self-activation of the application; • mechanisms ensuring the reliability of the VAMP system itself. Beyond implementing the solution, the most critical aspects of running VAMP have been formally verified using model checking tools. A validation step was also used to demonstrate the genericity of the proposal through various real-life implementations.

Durant ces dernières années, nous avons assisté à une forte émergence de nouvelles technologies et environnements informatiques tels que le cloud computing, l'informatique ubiquitaire ou les réseaux de capteurs. Ces environnements ont permis d'élaborer de nouveaux types d'applications avec une forte valeur ajoutée pour les usagés. Néanmoins, ils ont aussi soulevés de nombreux défis liés notamment à la conception, au déploiement et à la gestion de cycle de vie des applications. Ceci est dû à la nature même de ces environnements distribués, caractérisés par une grande flexibilité, un dynamisme accru et une forte hétérogénéité des ressources. L'objectif principal de cette thèse est de fournir une solution générique, réutilisable et extensible pour l'auto-gestion de ces applications. Nous nous sommes concentrés sur la fourniture d'un support logiciel permettant de gérer à l'exécution les architectures et leur cycle de vie, notamment pour les applications à base de composants s'exécutant dans des environnements dynamiques, distributes et à grande échelle. De façon à atteindre cet objectif, nous proposons une solution synergique – le framework Cube – combinant des techniques issues de domaines de recherche adjacents tels que l'auto-organisation, la satisfaction de contraintes, l'auto-adaptation et la reflexion fondée sur les modèles architecturaux. Dans notre solution, un ensemble de gestionnaires autonomiques décentralisés s'auto-organise de façon à construire et gérer une application cible en s'appuyant sur une description partagée des buts de l'application. Cette description formelle, appelé Archetype, prend la forme d'un graphe orienté exprimant les différents éléments de l'architecture et un ensemble de contraintes. Un prototype du framework Cube a été implanté dans le domaine particulier de la médiation. Des expériences ont été conduites dans le cadre de deux projets de recherché nationaux: Self-XL et Medical. Les résultats obtenus démontrent la validité de notre approche pour créer, réparer et adapter des applications à base de composants s'exécutant dans des environnements distribués, dynamiques et hétérogènes. / In recent years, the world has witnessed the rapid emergence of several novel technologies and computing environments, including cloud computing, ubiquitous computing and sensor networks. These environments have been rapidly capitalised upon for building new types of applications, and bringing added-value to users. At the same time, the resulting applications have been raising a number of new significant challenges, mainly related to system design, deployment and life-cycle management during runtime. Such challenges stem from the very nature of these novel environments, characterized by large scales, high distribution, resource heterogeneity and increased dynamism. The main objective of this thesis is to provide a generic, reusable and extensible self-management solution for these types of applications, in order to help alleviate this stringent problem. We are particularly interested in providing support for the runtime management of system architecture and life-cycle, focusing on applications that are component-based and that run in highly dynamic, distributed and large-scale environments. In order to achieve this goal, we propose a synergistic solution – the Cube framework – that combines techniques from several adjacent research domains, including self-organization, constraint satisfaction, self-adaptation and self-reflection based on architectural models. In this solution, a set of decentralised Autonomic Managers self-organize dynamically, in order to build and administer a target application, by following a shared description of administrative goals. This formal description, called Archetype, contains a graph-oriented specification of the application elements to manage and of various constraints associated with these elements. A prototype of the Cube framework has been implemented for the particular application domain of data-mediation. Experiments have been carried-out in the context of two national research projects: Self-XL and Medical. Obtained results indicate the viability of the proposed solution for creating, repairing and adapting component-based applications running in distributed volatile and evolving environments.

Les domaines de recherche actuels, tels que l'informatique ubiquitaire et l'informatique en nuage (cloud computing), considèrent que ces environnements d’exécution sont en changement continue. Les applications dynamiques, où les composants peuvent être ajoutés et supprimés pendant l'exécution, permettent à un logiciel de s'adapter et de s'ajuster à l'évolution des environnements, et de tenir compte de l’évolution du logiciel. Malheureusement, les applications dynamiques soulèvent des questions de conception et de développement qui n'ont pas encore été pleinement explorées.Dans cette thèse, nous montrons que le dynamisme est une préoccupation transversale qui rompt avec un grand nombre d’hypothèses que les développeurs d’applications classiques sont autorisés à prendre. Le dynamisme affecte profondément la conception et développement de logiciels. S'il n'est pas manipulé correctement, le dynamisme peut « silencieusement » corrompre l'application. De plus, l'écriture d'applications dynamiques est complexe et sujette à erreur. Et compte tenu du niveau de complexité et de l’impact du dynamisme sur le processus du développement, le logiciel ne peut pas devenir dynamique sans (de large) modification et le dynamisme ne peut pas être totalement transparent (bien que beaucoup de celui-ci peut souvent être externalisées ou automatisées).Ce travail a pour but d’offrir à l’architecte logiciel le contrôle sur le niveau, la nature et la granularité du dynamisme qui est nécessaire dans les applications dynamiques. Cela permet aux architectes et aux développeurs de choisir les zones de l'application où les efforts de programmation des composants dynamiques seront investis, en évitant le coût et la complexité de rendre tous les composants dynamiques. L'idée est de permettre aux architectes de déterminer l'équilibre entre les efforts à fournir et le niveau de dynamisme requis pour les besoins de l'application. / Current areas of research, such as ubiquitous and cloud computing, consider execution environments to be in a constant state of change. Dynamic applications—where components can be added, removed and substituted during execution—allow software to adapt and adjust to changing environments, and to accommodate evolving features. Unfortunately, dynamic applications raise design and development issues that have yet to be fully addressed. In this dissertation we show that dynamism is a crosscutting concern that breaks many of the assumptions that developers are otherwise allowed to make in classic applications. Dynamism deeply impacts software design and development. If not handled correctly, dynamism can silently corrupt the application. Furthermore, writing dynamic applications is complex and error-prone, and given the level of complexity and the impact dynamism has on the development process, software cannot become dynamic without (extensive) modification and dynamism cannot be entirely transparent (although much of it may often be externalized or automated). This work focuses on giving the software architect control over the level, the nature and the granularity of dynamism that is required in dynamic applications. This allows architects and developers to choose where the efforts of programming dynamic components are best spent, avoiding the cost and complexity of making all components dynamic. The idea is to allow architects to determine the balance between the efforts spent and the level of dynamism required for the application's needs. At design-time we perform an impact analysis using the architect's requirements for dynamism. This serves to identify components that can be corrupted by dynamism and to—at the architect's disposition—render selected components resilient to dynamism. The application becomes a well-defined mix of dynamic areas, where components are expected to change at runtime, and static areas that are protected from dynamism and where programming is simpler and less restrictive. At runtime, our framework ensures the application remains consistent—even after unexpected dynamic events—by computing and removing potentially corrupt components. The framework attempts to recover quickly from dynamism and to minimize the impact of dynamism on the application. Our work builds on recent Software Engineering and Middleware technologies—namely, OSGi, iPOJO and APAM—that provide basic mechanisms to handle dynamism, such as dependency injection, late-binding, service availability notifications, deployment, lifecycle and dependency management. Our approach, implemented in the Robusta prototype, extends and complements these technologies by providing design and development-time support, and enforcing application execution consistency in the face of dynamism.

La gestion de l'acheminement de messages d'e-santé en environnement ubiquitaire soulève plusieurs défis majeurs liés à la diversité et à la spécificité des cas d'usage et des acteurs, à l'évolutivité des contextes médical, social, logistique, environnemental...Nous proposons une méthode originale d'orchestration autonome et auto-adaptative de services visant à optimiser le flux des messages et à personnaliser la qualité de transmission, en les adressant aux destinataires les plus appropriés dans les délais requis. Notre solution est une architecture générique dirigée par des modèles du domaine d'information considéré et des données contextuelles, basés sur l'identification des besoins et des contraintes soulevées par notre problématique.Notre approche consiste en la composition de services de fusion et de gestion dynamique en temps réel d'informations hétérogènes provenant des écosystèmes source, cible et message, pilotés par des méthodes d'intelligence artificielle pour l'aide à la prise de décision de routage. Le but est de garantir une communication fiable, personnalisable et sensible à l'évolution du contexte, quel que soit le scénario et le type de message (alarme, technique, etc.). Notre architecture, applicable à divers domaines, a été consolidée par une modélisation des processus métiers (BPM) explicitant le fonctionnement des services qui la composent.Le cadriciel proposé est basé sur des ontologies et est compatible avec le standard HL7 V3. L'auto-adaptation du processus décisionnel d'acheminement est assurée par un réseau bayésien dynamique et la supervision du statut des messages par une modélisation mathématique utilisant des réseaux de Petri temporels / Routing policy management of eHealth messages in ubiquitous environment leads to address several key issues, such as taking into account the diversity and specificity of the different use cases and actors, as well as the dynamicity of the medical, social, logistic and environmental contexts.We propose an original, autonomous and adaptive service orchestration methodology aiming at optimizing message flow and personalizing transmission quality by timely sending the messages to the appropriate recipients. Our solution consists in a generic, model-driven architecture where domain information and context models were designed according to user needs and requirements. Our approach consists in composing, in real time, services for dynamic fusion and management of heterogeneous information from source, target and message ecosystems, driven by artificial intelligence methods for routing decision support. The aim is to ensure reliable, personalized and dynamic context-aware communication, whatever the scenario and the message type (alarm, technical, etc.). Our architecture is applicable to various domains, and has been strengthened by business process modeling (BPM) to make explicit the services operation.The proposed framework is based on ontologies and is compatible with the HL7 V3 standard. Self-adaptation of the routing decision process is performed by means of a dynamic Bayesian network and the messages status supervision is based on timed Petri nets

Made available in DSpace on 2016-08-17T14:53:28Z (GMT). No. of bitstreams: 1 Dissertacao Eduardo Henrique.pdf: 3617295 bytes, checksum: 9340e7d8d280cd0e83cf78ad24f4e7b8 (MD5) Previous issue date: 2013-11-26 / Conselho Nacional de Desenvolvimento Científico e Tecnológico / Cloud computing is a new computing paradigm which aims to provide on-demand service. Characteristics such as scalability and availability of infinite resources have attracted many users and companies. As they come along too many malicious users who want to take advantage of this possibility of resource sharing. Also migration networks and servers for cloud means hacking techniques are now destined to cloud-based servers. Attacks can originate until even within the environment, when a virtual machine that is being performed on one of his Vlans is used to probe, capture data or insert server attacks that are instantiated in the cloud. All this combined with a difficult to administer due to the complexity of the infrastructure leaves the safety of the environment to be a critical point. The purpose of this study is to use an autonomic framework with a methodology for disappointment to propose a security model for autonomic computing clouds that assist in the security of servers and instances works against attacks from other instances. / A Computação em Nuvem é um novo paradigma da computação que visa oferecer serviço sob demanda. Suas características como escalabilidade e disponibilidade de recursos infinitos vêm atraindo muitos usuários e empresas. Junto como eles vem também muitos usuários mal intencionados que querem se aproveitar dessa possibilidade de compartilhamento de recurso. Também migração de redes e servidores para nuvem significa que técnicas de invasão estão agora destinados a servidores baseados em nuvem . Ataques podem ser originados ate mesmo dentro do ambiente, quando uma de máquina virtual que esta sendo executada em uma de suas Vlans é utilizada para sondar, capturar dados ou inserir ataques a servidores que estão instanciados na nuvem. Tudo isso aliado a uma difícil administração devido à complexidade da infraestrutura do ambiente deixa a segurança sendo um ponto critico. A proposta desse trabalho é utilizar um framework autonômico juntamente com uma metodologia de decepção para propor um modelo segurança autonômica para nuvens computacionais que auxiliem na segurança de servidores e instâncias works contra ataques oriundos de outras instâncias.

Dans ce mémoire de thèse, nous présentons une approche d’exécution auto-corrective (self-healing) de services composites, basée sur des agents capables de prendre, de manière autonome, des décisions pendant l’exécution des services, à partir de leurs connaissances. Dans un premier temps, nous définissons, de manière formelle, en utilisant des réseaux de Petri colorés, les services composites, leur processus d’exécution, et leurs mécanismes de tolérance aux pannes. Notre approche offre plusieurs mécanismes de reprise sur panne alternatifs : la récupération en arrière avec compensation ; la récupération en avant avec ré-exécution et/ou remplacement de service ; et le point de contrôle (checkpointing), à partir duquel il est possible de reprendre l’exécution du service ultérieurement. Dans notre approche, les services sont contrôlés par des agents, i.e. des composants dont le rôle est de s’assurer que l’exécution des services soit tolérante aux pannes. Notre approche est également étendue afin de permettre un auto-recouvrement. Dans cette extension, les agents disposent d’une base de connaissances contenant à la fois des informations sur eux-mêmes et sur le contexte d’exécution. Pour prendre des décisions concernant la sélection des stratégies de récupération, les agents font des déductions en fonction des informations qu’ils ont sur l’ensemble du service composite, sur eux-mêmes, tout en prenant en compte également ce qui est attendu et ce qui se passe réellement lors de l’exécution. Finalement, nous illustrons notre approche par une évaluation expérimentale en utilisant un cas d’étude. / In this thesis, we present a self-healing approach for composite services supported by knowledge-based agents capable of making decisions at runtime. First, we introduce our formal definition of composite services, their execution processes, and their fault tolerance mechanisms using Colored Petri nets. We implement the following recovery mechanisms: backward recovery through compensation; forward recovery through service retry and service replacement; and checkpointing as an alternative strategy. We introduce the concept of Service Agents, which are software components in charge of component services and their fault tolerance execution control. We then extend our approach with self-healing capabilities. In this self-healing extension, Service Agents are knowledge-based agents; that is, they are self- and context-aware. To make decisions about the selection of recovery and proactive fault tolerance strategies, Service Agents make deductions based on the information they have about the whole composite service, about themselves, and about what is expected and what it is really happening at runtime. Finally, we illustrate our approach and evaluate it experimentally using a case study.

L’informatique en nuage, au travers de son modèle en couche et de l’accès à ses services à la demande, a bouleversé la façon de gérer les infrastructures (IaaS) et la manière de produire les logiciels (SaaS). Grâce à l’élasticité de l’infrastructure, la quantité de ressource peut être ajustée automatiquement en fonction de la demande afin de satisfaire un certain niveau de qualité de service (QoS) aux clients tout en minimisant les coûts d’exploitation sous-jacents. Le modèle d’élasticité actuel qui consiste à ajuster les ressources IaaS au travers de services de dimensionnement automatique basiques montre ses limites en termes de réactivité et de granularité d’adaptation. De plus, bien qu’étant une caractéristique cruciale de l’informatique en nuage, l’élasticité est à ce jour pauvrement outillée empêchant ainsi les différents acteurs du Cloud de jouir pleinement de ses bienfaits. Dans ce travail de thèse, nous proposons d’étendre leconcept d’élasticité aux couches hautes du nuage, et plus précisément au niveau du SaaS. Nous présentons ainsi le nouveau concept d’élasticité logicielle que nous définissons comme la capacité d’un logiciel à s’adapter, idéalement de manière autonome, pour répondre aux changements de la demande et/ou aux limitations de l’élasticité des ressources de l’infrastructure. Il s’agit alors d’envisager l’élasticité de manière transverse et multi-couche en considérant l’adaptation des ressources Cloud au sens large. Pour ce faire, nous présentons un modèle pour la gestion autonome de l’élasticité multi-couche et le Framework ElaStuff associé. Dans le but d’outiller et d’industrialiser le processus de gestion de l’élasticité, nous proposons l’outil de surveillance perCEPtion basé sur le traitement des événements complexes et permettant à l’administrateur de mettre en place une observation avancée du système Cloud. De plus, un langage dédié à l’élasticité multi-couche nommé ElaScript est proposé pour exprimer simplement et efficacement des plans de reconfiguration orchestrant les actions d’élasticité de différents niveaux. Enfin, notre proposition d’étendre l’élasticité aux couches hautes du Cloud, et plus particulièrement au niveau SaaS, est validée expérimentalement selon plusieurs points devue (QoS, énergie, réactivité et précision du passage à l’échelle,etc.). / Cloud computing, through its layered model and access to its on-demand services, has changed the way of managing the infrastructures (IaaS) and how to produce software (SaaS). With the advent of IaaS elasticity, the amount of resources can be automatically adjusted according to the demand to satisfy a certain level of quality of service (QoS) to customers while minimizing underlying operating costs. The current elasticity model is based on adjusting the IaaS resources through basic autoscaling services, which reaches to its limit in terms of responsiveness and adaptation granularity. Although it is an essential feature for Cloud computing, elasticity remains poorly equipped which prevents the various actors of the Cloud to really enjoy its benefits. In this thesis, we propose to extend the concept of elasticity to higher layers of the cloud, and more precisely to the SaaS level. Then, we present the new concept of software elasticity by defining the ability of the software to adapt, ideally in an autonomous way, to cope with workload changes and/or limitations of IaaS elasticity. This predicament brings the consideration of Cloud elasticity in a multi-layer way through the adaptation of all kind of Cloud resources. To this end, we present a model for the autonomic management of multi-layer elasticity and the associated framework ElaStuff. In order to equip and industrialize the elasticity management process, we propose the perCEPtion monitoring tool, based on complex event processing, which enables the administrators to set up an advanced observation of the Cloud system. In addition, we propose a domain specific language (DSL) for the multi-layer elasticity, called ElaScript, which allows to simply and effectively express reconfiguration plans orchestrating the different levels of elasticity actions. Finally, our proposal to extend the Cloud elasticity to higher layers, particularly to SaaS,is validated experimentally from several perspectives (QoS,energy, responsiveness and accuracy of the scaling, etc.).

A evolução de sistemas distribuídos resultou em aumento significativo de complexidade para manutenção e gerenciamento, tornando pouco eficientes técnicas convencionais baseadas em intervenções manuais. Isso motivou pesquisas que deram origem ao paradigma de computação autônoma (Autonomic Computing), que provê aspectos de auto-configuração, auto-recuperação, auto-otimização e auto-proteção a fim de tornar sistemas auto-gerenciáveis. Nesse contexto, esta tese teve como objetivo prover autonomia a ambientes distribuídos, sem a necessidade de mudar o paradigma de programação e as aplicações de usuários. Para isso, propôs-se uma abordagem que emprega técnicas para compreensão e predição de dinâmicas comportamentais de processos, utilizando abordagens de sistemas dinâmicos, inteligência artificial e teoria do caos. Os estudos realizados no decorrer desta pesquisa demonstraram que, ao predizer padrões comportamentais, pode-se otimizar diversos aspectos de computação distribuída, suportando tomadas de decisão autônomas pelos ambientes. Para validar a abordagem proposta, foi desenvolvida uma política de escalonamento distribuído, denominada PredRoute, a qual utiliza o conhecimento sobre o comportamento de processos para otimizar, transparentemente, a alocação de recursos. Experimentos realizados demonstraram que essa política aumenta o desempenho em até 4 ordens de grandeza e apresenta baixo custo computacional, o que permite a sua adoção para escalonamento online de processos / The evolution of distributed systems resulted in a significant growth in management and support complexities, which uncovered the inefficiencies incurred by the usage of conventional management techniques, based in manual interventions. This, therefore, has motivated researches towards the concept of Autonomic Computing, which provides aspects of self-configuration, self-healing, self-optimization and self-protection, aiming at developing computer systems capable of self-management. In this context, this thesis was conceived with the goal of providing autonomy to distributed systems, without changing the programming paradigm or user applications. In order to reach this goal, we proposed an approach which employs techniques capable of modelling and predicting the dynamics of application behavior, using concepts introduced in dynamical systems, artificial intelligence, and chaos theory. The obtained results demonstrated that it is possible to optimize several aspects of distributed computing, providing support for autonomic computing capabilities to distributed environments. In order to validate the proposed approach, a distributed scheduling policy was developed, named PredRoute, which uses the knowledge about the process behavior to transparently optimize the resource allocation. Experimental results demonstrated that this policy can improve the system performance by up to a power of 4, and also requires a considerably low computational cost, which suggests its adoption for online process scheduling in distributed environments