L’informatique en nuage révolutionne complètement la façon de gérer les ressources. Grâce à l’élasticité, les ressources peuvent être provisionnées en quelques minutes pour satisfaire un niveau de qualité de service (QdS) formalisé par un accord de niveau de service (SLA) entre les différents acteurs du nuage. Le principal défi des fournisseurs de services est de maintenir la satisfaction de leurs consommateurs tout en minimisant le coût de ces services. Du point de vue SaaS, ce défi peut être résolu d’une manière ad-hoc par l’allocation/-libération des ressources selon un ensemble de règles prédéfinies avec Amazon Auto Scaling par exemple. Cependant, implémenter finement ces règles d’élasticité n’est pas une tâche triviale. D’une part, la difficulté de profiler la performance d’un service compromet la précision de la planification des ressources. D’autre part, plusieurs paramètres doivent être pris en compte, tels que la multiplication des types de ressources, le temps non-négligeable d’initialisation de ressource et le modèle de facturation IaaS. Cette thèse propose une solution complète pour la gestion des contrats de service du nuage. Nous introduisons CSLA (Cloud ServiceLevel Agreement), un langage dédié à la définition de contrat de service en nuage. Il adresse finement les violations SLA via la dégradation fonctionnelle/QdS et des modèles de pénalité avancés. Nous proposons, ensuite, HybridScale un framework de dimensionnement automatique dirigé par les SLA. Il implémente l’élasticité de façon hybride : gestion réactive-proactive, dimensionnement vertical horizontal et multi-couches (application-infrastructure). Notre solution est validée expérimentalement sur Amazon EC2. / Cloud computing promises to completely revolutionize the way to manage resources. Thanks to elasticity, resources can be provisioning within minutes to satisfy a required level of Quality of Service(QoS) formalized by Service Level Agreements (SLAs) between different Cloud actors. The main challenge of service providers is to maintain its consumer’s satisfaction while minimizing the service costs due to resources fees. For example, from the SaaS point of view, this challenge can be achieved in ad-hoc manner by allocating/releasing resources based on a set of predefined rules as Amazon Auto Scaling implements it. However, doing it right –in a way that maintains end-users satisfaction while optimizing service cost– is not a trivial task. First, because of the difficulty to profile service performance,the accuracy of capacity planning may be compromised. Second, several parameters should be taken into account such as multiple resource types, non-ignorable resource initiation time and IaaS billing model. For that purpose, we propose a complete solution for Cloud Service Level Management. We first introduce CSLA (Cloud Service LevelAgreement), a specific language to describe SLA for Cloud services. It finely expresses SLA violations via functionality/QoS degradationand an advanced penalty model. Then, we propose HybridScale, an auto-scaling framework driven by SLA. It implements the Cloud elasticity in a triple hybrid way : reactive-proactive management, vertical horizontal scaling at cross-layer (application-infrastructure). Our solution is experimentally validated on Amazon EC2.

O paradigma de computação em nuvem, por meio de seus modelos de serviço e implantação, apresenta para os provedores de serviço e consumidores benefícios e desafios. Um dos principais desafios apontados pela área de computação em nuvem é com relação à segurança da informação, especificamente a questão de conformidade com relação a contratos firmados entre o provedor e o consumidor. O acordo de nível de serviço (SLA) é um destes contratos, no qual são estabelecidos requisitos para a entrega e operação do serviço contratado pelo consumidor, bem como penalidades em caso de não atendimento a requisitos estabelecidos no contrato. Comumente, em um SLA definido entre provedor de serviço e consumidor as necessidades de disponibilidade e desempenho com relação ao serviço contratado são especificados, o que não ocorre com relação às necessidades de segurança. A necessidade de especificação de requisitos de segurança em um SLA, em especial confidencialidade e integridade, para o contexto de computação em nuvem, bem como arquiteturas de computação que tratem de requisitos de segurança em um SLA e efetuem o gerenciamento destes requisitos durante o ciclo de vida do SLA, encontram-se em evolução, se comparado aos requisitos de disponibilidade. Considerando a demanda crescente de incorporação de SLA de Segurança nos contratos de serviços de computação em nuvem, este trabalho tem como objetivo propor e avaliar um arcabouço de gerenciamento de serviços de computação em nuvem para o modelo de infraestrutura como serviço (IaaS), tendo como base requisitos de segurança especificados em um SLA, em especial os requisitos de confidencialidade e integridade. O gerenciamento proposto pelo arcabouço contempla as etapas do ciclo de vida de um SLA, que compreende as fases de: i) definir e especificar o SLA; ii) gerenciar e implantar o SLA; iii) executar e gerenciar o SLA e iv) finalizar o SLA. A validação do arcabouço proposto é realizada por meio da sua aplicação em um cenário de uso, onde será verificado o atendimento aos requisitos de segurança definidos e especificados no SLA. Para assegurar que o arcabouço proposto é seguro, bem como a sua integração com o ambiente de computação em nuvem é realizada análise de ameaças do arcabouço, e ações de mitigação apresentadas. Ao final, mostra-se que o arcabouço de gerenciamento proposto cumpre com os objetivos e requisitos propostos. / The cloud computing paradigm given its service and deployment models presents several benefits and challenges. One of the main challenges is related to information security, in particular, the compliance contracts between consumers and service provider. Service Level Agreements (SLAs) are contracts in which requirements about service operation and delivery as well as penalties in case of non-compliance of these requirements are defined. A SLA is usually defined in terms of availability and performance requirements, and data security requirements are normally not specified in details as these requirements. The need for security requirements specified in an SLA, especially confidentiality and integrity to the cloud computing paradigm, as well computing architectures to deal with SLA security requirements and management of cloud services based on SLA security requirements in an automated manner during its entire lifecycle are still in evolution, compared to availability requirements. In order to deal with these ineeds, this work aims to propose and evaluate a framework to orchestrate the management of cloud services for the infrastructure as a service (IaaS) based on SLA security requirements, specifically the confidentiality and integrity requirements. The management proposed by the framework comprehend the steps of the SLA lifecycle: i) SLA specification and definition; ii) SLA deployment and management; iii) SLA execute and monitoring; and iv) SLA termination. The validation of proposed framework is performed by its application in a usage scenario, checking the compliance with defined security requirements and specified in the SLA. To ensure the security of proposed framework and its cloud computing environment integration, a threat modeling is performed and mitigation actions are presented. At last, it is shown that the proposed management framework meets the specified framework requirements.

<p> <p>&nbsp / </p> </p> <p align="left">The underlying theme of this thesis is identification, classification, detection and prediction of cellular network faults using state of the art technologies, methods and algorithms.</p>

In mobile and wireless networks, data broadcasting for popular data items enables the efficient utilization of the limited wireless bandwidth. However, efficient data scheduling schemes are needed to fully exploit the benefits of data broadcasting. Towards this goal, several broadcast scheduling policies have been proposed. These existing schemes have mostly focused on either minimizing response time, or drop rate, when requests are associated with hard deadlines. The inherent inaccuracy of hard deadlines in a dynamic mobile environment motivated us to use Service Level Agreements (SLAs) where a user specifies the utility of data as a function of its arrival time. Moreover, SLAs provide the mobile user with an already familiar quality of service specification from wired environments. Hence, in this dissertation, we propose SAAB, an SLA-aware adaptive data broadcast scheduling policy for maximizing the system utility under SLA-based performance measures. To achieve this goal, SAAB considers both the characteristics of disseminated data objects as well as the SLAs associated with them. Additionally, SAAB automatically adjusts to the system workload conditions which enables it to constantly outperform existing broadcast scheduling policies.

In mobile and wireless networks, data broadcasting for popular data items enables the efficient utilization of the limited wireless bandwidth. However, efficient data scheduling schemes are needed to fully exploit the benefits of data broadcasting. Towards this goal, several broadcast scheduling policies have been proposed. These existing schemes have mostly focused on either minimizing response time, or drop rate, when requests are associated with hard deadlines. The inherent inaccuracy of hard deadlines in a dynamic mobile environment motivated us to use Service Level Agreements (SLAs) where a user specifies the utility of data as a function of its arrival time. Moreover, SLAs provide the mobile user with an already familiar quality of service specification from wired environments. Hence, in this dissertation, we propose SAAB, an SLA-aware adaptive data broadcast scheduling policy for maximizing the system utility under SLA-based performance measures. To achieve this goal, SAAB considers both the characteristics of disseminated data objects as well as the SLAs associated with them. Additionally, SAAB automatically adjusts to the system workload conditions which enables it to constantly outperform existing broadcast scheduling policies.

No description available.

<p> <p>&nbsp / </p> </p> <p align="left">The underlying theme of this thesis is identification, classification, detection and prediction of cellular network faults using state of the art technologies, methods and algorithms.</p>

Les centres de données verts de dernière génération ont été conçus pour une consommation optimisée et une meilleure qualité du niveau de service SLA. Cependant,ces dernières années, le marché des centres de données augmente rapidement,et la concentration de la puissance de calcul est de plus en plus importante, ce qui fait augmenter les besoins en puissance électrique et refroidissement. Un centre de données est constitué de ressources informatiques, de systèmes de refroidissement et de distribution électrique. De nombreux travaux de recherche se sont intéressés à la réduction de la consommation des centres de données afin d'améliorer le PUE, tout en garantissant le même niveau de service. Certains travaux visent le dimensionnement dynamique des ressources en fonction de la charge afin de réduire le nombre de serveurs démarrés, d'autres cherchent à optimiser le système de refroidissement qui représente un part important de la consommation globale.Dans cette thèse, afin de réduire le PUE, nous étudions la mise en place d'un système autonome d'optimisation globale du refroidissement, qui se base sur des sources de données externes tel que la température extérieure et les prévisions météorologiques, couplé à un module de prédiction de charge informatique globale pour absorber les pics d'activité, pour optimiser les ressources utilisés à un moindre coût, tout en préservant la qualité de service. Afin de garantir un meilleur SLA, nous proposons une architecture distribuée pour déceler les anomalies de fonctionnements complexes en temps réel, en analysant de gros volumes de données provenant des milliers de capteurs du centre de données. Détecter les comportements anormaux au plus tôt, permet de réagir plus vite face aux menaces qui peuvent impacter la qualité de service, avec des boucles de contrôle autonomes qui automatisent l'administration. Nous évaluons les performances de nos contributions sur des données provenant d'un centre de donnée en exploitation hébergeant des applications réelles. / Next-generation green datacenters were designed for optimized consumption and improved quality of service level Service Level Agreement (SLA). However, in recent years, the datacenter market is growing rapidly, and the concentration of the computing power is increasingly important, thereby increasing the electrical power and cooling consumptions. A datacenter consists of computing resources, cooling systems, and power distribution. Many research studies have focused on reducing the consumption of datacenters to improve the PUE, while guaranteeing the same level of service. Some works aims the dynamic sizing of resources according to the load, to reduce the number of started servers, others seek to optimize the cooling system which represents an important part of total consumption. In this thesis, in order to reduce the PUE, we study the design of an autonomous system for global cooling optimization, which is based on external data sources such as the outside temperature and weather forecasting, coupled with an overall IT load prediction module to absorb the peaks of activity, to optimize activere sources at a lower cost while preserving service level quality. To ensure a better SLA, we propose a distributed architecture to detect the complex operation anomalies in real time, by analyzing large data volumes from thousands of sensors deployed in the datacenter. Early identification of abnormal behaviors, allows a better reactivity to deal with threats that may impact the quality of service, with autonomous control loops that automate the administration. We evaluate the performance of our contributions on data collected from an operating datacenter hosting real applications.

Le Cloud Computing est en plein essor, grace a ses divers avantages, telsl'elasticite, le cout, ou encore son importante exibilite dans le developpementd'applications. Il demeure cependant des problemes en suspens, lies auxperformances, a la disponibilite, la fiabilite, ou encore la securite. De nombreusesetudes se focalisent sur la fiabilite et les performance dans les servicesdu Cloud, qui sont les points critiques pour le client. On retrouve parmicelles-ci plusieurs themes emergents, allant de l'ordonnancement de tachesau placement de donnees et leur replication, en passant par la tolerance auxfautes adaptative ou a la demande, et l'elaboration de nouveaux modeles defautes.Les outils actuels evaluant la fiabilite des services du Cloud se basent surdes parametres simplifies. Ils ne permettent pas d'analyser les performancesou de comparer l'efficacite des solutions proposees. Cette these aborde precisement ce probleme en proposant un modele d'environnement complet detest destine a evaluer la fiabilite et les performances des services de CloudComputing. La creation d'outils de tests destines a l'evaluation de la fiabiliteet des performances des services du Cloud pose de nombreux defis, en raisonde la grande quantite et de la complexite des donnees traitees par ce genrede services. Les trois principaux modeles de Cloud Computing sont respectivement:Infrastructure en tant que Service (IaaS), Plate-forme en tant queService (PaaS) et Logiciel en tant que Service (SaaS).Dans le cadre de cettethese, nous nous concentrons sur le modele PaaS. Il permet aux systemesd'exploitation ou aux intergiciels d'etre accessibles via une connexion internet.Nous introduisons une architecture de test generique, qui sera utiliseepar la suite lors de la creation d'outils de tests, destines a l'evaluation de lafiabilite et de la performance. / Cloud computing models are attractive because of various benefits such asscalability, cost and exibility to develop new software applications. However,availability, reliability, performance and security challenges are still not fullyaddressed. Dependability is an important issue for the customers of cloudcomputing who want to have guarantees in terms of reliability and availability.Many studies investigated the dependability and performance of cloud services,ranging from job scheduling to data placement and replication, adaptiveand on-demand fault-tolerance to new fault-tolerance models. However, thead-hoc and overly simplified settings used to evaluate most cloud service fault toleranceand performance improvement solutions pose significant challengesto the analysis and comparison of the effectiveness of these solutions.This thesis precisely addresses this problem and presents a benchmarkingapproach for evaluating the dependability and performance of cloud services.Designing of dependability and performance benchmarks for a cloud serviceis a particular challenge because of high complexity and the large amount ofdata processed by such service. Infrastructure as a Service (IaaS), Platform asa Service (PaaS) and Software as a Service (SaaS) are the three well definedmodels of cloud computing. In this thesis, we will focus on the PaaS modelof cloud computing. PaaS model enables operating systems and middlewareservices to be delivered from a managed source over a network. We introduce ageneric benchmarking architecture which is further used to build dependabilityand performance benchmarks for PaaS model of cloud services.

With Cloud Computing becoming a popular term on the Information Technology (IT) market, security and accountability has become important issues to highlight. In our research we review these concepts by focusing on security risks with Cloud Computing and the associated services; Software, Platform and Infrastructure (SPI) and connecting them with a social study of trust. The method that was conducted during our research was reviewing secondary literature, interviewing different experts regarding Cloud Computing and relating standards already established by ENISA, NIST, and CSA to the interviews. The result of this study shows connections between the specific SPIs, both how they compare, but also how they differ. In the end we were also able to rank the top security risks from interviews with experts and see which SPI could be the most insecure one and  what countermeasures could be applied. This was further related to trust and Service Level Agreement (SLA) in Cloud Computing to show how the security risks we discuss are related to these two specific areas. By highlighting this we wanted to present useable information for both clients and providers in how to create a better Cloud Computing environment.