The Challenge of Cloud Control

Today’s cloud data center infrastructures are not even near being able to cope with the enormous and rapidly varying capacity demands that will be reality in a near future. So far, very little is understood about how to transform today’s data centers (being large, power-hungry facilities, and operated through heroic efforts by numerous administrators) into a self-managed, dynamic, and dependable infrastructure, constantly delivering expected QoS with reasonable operation costs and acceptable carbon footprint for large-scale services with sometimes dramatic variations in capacity demands. In this paper, we discuss some of the major challenges for resource-optimized cloud data center. We propose a new research area called Cloud Control, which is a control theoretic approach to a range of cloud management problems, aiming to transform today´s static and energy consuming cloud data centers into self-managed, dynamic, and dependable infrastructures, constantly delivering expected quality of service with acceptable operation costs and carbon footprint for large-scale services with varying capacity demands

Approche dirigée par les contrats de niveaux de service pour la gestion de l'élasticité du "nuage"

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 horizontalet 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.NANTES-ENS Mines (441092314) / SudocSudocFranceF

Cloud Broker Based Trust Assessment of Cloud Service Providers

Cloud computing is emerging as the future Internet technology due to its advantages such as sharing of IT resources, unlimited scalability and flexibility and high level of automation. Along the lines of rapid growth, the cloud computing technology also brings in concerns of security, trust and privacy of the applications and data that is hosted in the cloud environment. With large number of cloud service providers available, determining the providers that can be trusted for efficient operation of the service deployed in the provider’s environment is a key requirement for service consumers. In this thesis, we provide an approach to assess the trustworthiness of the cloud service providers. We propose a trust model that considers real-time cloud transactions to model the trustworthiness of the cloud service providers. The trust model uses the unique uncertainty model used in the representation of opinion. The Trustworthiness of a cloud service provider is modelled using opinion obtained from three different computations, namely (i) compliance of SLA (Service Level Agreement) parameters (ii) service provider satisfaction ratings and (iii) service provider behaviour. In addition to this the trust model is extended to encompass the essential Cloud characteristics, credibility for weighing the feedbacks and filtering mechanisms to filter the dubious feedback providers. The credibility function and the early filtering mechanisms in the extended trust model are shown to assist in the reduction of impact of malicious feedback providers

Probabilistic Admission Control for Elastic Cloud Computing

Abstract—This paper tackles the problem of optimum allocation of elastic services on virtualized physical resources by incorporating a probabilistic approach in terms of availability guarantees, which allows for reducing the physical computational resources that are required for elasticity reasons. The resulting probabilistic optimization problem also allows for proper trade-offs among business level objectives. Its output is the set of the admitted services, as well as the allocated computing capacity for each service component that comprise the services on the selected physical hosts. The problem was modeled on the General Algebraic Modeling System (GAMS) and solved under realistic provider’s settings that demonstrate the efficiency of the proposed method. Keywords-admission control; elasticity; cloud computing; optimum allocation. I