Towards QoS-Oriented SLA Guarantees for Online Cloud Services

International audienceCloud Computing provides a convenient means of remote on-demand and pay-per-use access to computing resources. However, its ad hoc management of quality-of-service and SLA poses significant challenges to the performance, dependability and costs of online cloud services. The paper precisely addresses this issue and makes a threefold contribution. First, it introduces a new cloud model, the SLAaaS (SLA aware Service) model. SLAaaS enables a systematic integration of QoS levels and SLA into the cloud. It is orthogonal to other cloud models such as SaaS or PaaS, and may apply to any of them. Second, the paper introduces CSLA, a novel language to describe QoS-oriented SLA associated with cloud services. Third, the paper presents a control-theoretic approach to provide performance, dependability and cost guarantees for online cloud services, with time-varying workloads. The proposed approach is validated through case studies and extensive experiments with online services hosted in clouds such as Amazon EC2. The case studies illustrate SLA guarantees for various services such as a MapReduce service, a cluster-based multi-tier e-commerce service, and a low-level locking service

Insurance for Improving User Satisfaction Level

Service-level agreement (SLA) violations may lead to losses and user dissatisfaction. Despite the fact that a service guarantee can increase the satisfaction level of users, indemnities may not be commensurate with the importance of a service to a user. While predefined penalties may be insufficient to compensate for the losses of one user, another user may not suffer loss from the SLA violation. With an insurance plan, an insurer can reach an agreement with users on the premium and loss coverage volume; insurance can therefore be considered a solution for providing indemnity which is appropriate to the importance of service. An insurer cannot protect users against these losses, which are caused by a single root event, in the same way as it protects them against the losses caused by independent events. In this paper, a novel approach is proposed for providing insurance coverage for such root events by limiting insurance provisions to the users with the highest priority. A criterion is presented for priority assignment to users, and an algorithm is then proposed for providing insurance according to this priority. A game-theoretic analysis is also provided to assess acceptability of the outcome of the proposed algorithm to rational users and insurers. The results of numerical experiments demonstrate the usefulness of the proposed approach for improving the utility of the Service

ADVANCED SLA MANAGEMENT IN CLOUD COMPUTING

The advent of high-performance technologies and the increase in volume of data used by organizations led to the need for migration from an internal structure to Cloud environment. The continuous development of tools, methods and techniques have expanded the understanding of the various functions, structures and processes related to Cloud Computing. However, the increase in computing power led to the development and use of more complex models, including this scope the complexity of Service Level Agreements (SLA). The need for understanding at a high level of SLAs established between customers and service providers in Cloud led to different studies on the definition and standardization of these agreements. Nowadays, cloud computing technologies are becoming more and more popular, especially with respect to data storage. However, the processes used to determine the Cloud Service Agreements do not consider the final customer\u2019s needs, considering only the supply capacity of the service provider. For these reasons, the development of service agreements that meets the needs of customers should be designed in order to increase the usability of Cloud environments, and enabling the discovery of new areas of application in accordance with market demand. In this context, the use of ontologies that describes the information that composes each type of service, and thus enable an understanding of the agreements reached, is configured as an approach to be considered. Moreover, the generalization and abstraction of information that can be observed in different services allows a broader vision for managing SLAs. For these reasons, this thesis aims to find innovative methods for the composition of Service Level Agreements in Cloud Computing. In particular, the methods presented allow demonstrate the convergence of several consolidated techniques in research on Cloud SLA using a new approach that considers new demands on Cloud and allows control of the established agreements, in addition to effectively ensure the application of the concept of XaaS (everything as a service). The originality of the approach allows the registration, search, composition and control of services in Cloud using the same structure. The new approach presented in this thesis allows the understanding of the impact of the new services requested by customers, giving the provider the possibility of simulating the use of the necessary resources to meet the new services\u2019 requests. From the presentation of a conceptual framework we can demonstrate the use of our approach through the examples of different situations presented in the real world and considering the new market possibilities

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

Service level agreement specification for IoT application workflow activity deployment, configuration and monitoring

PhD ThesisCurrently, we see the use of the Internet of Things (IoT) within various domains such as healthcare, smart homes, smart cars, smart-x applications, and smart cities. The number of applications based on IoT and cloud computing is projected to increase rapidly over the next few years. IoT-based services must meet the guaranteed levels of quality of service (QoS) to match users’ expectations. Ensuring QoS through specifying the QoS constraints using service level agreements (SLAs) is crucial. Also because of the potentially highly complex nature of multi-layered IoT applications, lifecycle management (deployment, dynamic reconfiguration, and monitoring) needs to be automated. To achieve this it is essential to be able to specify SLAs in a machine-readable format. currently available SLA specification languages are unable to accommodate the unique characteristics (interdependency of its multi-layers) of the IoT domain. Therefore, in this research, we propose a grammar for a syntactical structure of an SLA specification for IoT. The grammar is based on a proposed conceptual model that considers the main concepts that can be used to express the requirements for most common hardware and software components of an IoT application on an end-to-end basis. We follow the Goal Question Metric (GQM) approach to evaluate the generality and expressiveness of the proposed grammar by reviewing its concepts and their predefined lists of vocabularies against two use-cases with a number of participants whose research interests are mainly related to IoT. The results of the analysis show that the proposed grammar achieved 91.70% of its generality goal and 93.43% of its expressiveness goal. To enhance the process of specifying SLA terms, We then developed a toolkit for creating SLA specifications for IoT applications. The toolkit is used to simplify the process of capturing the requirements of IoT applications. We demonstrate the effectiveness of the toolkit using a remote health monitoring service (RHMS) use-case as well as applying a user experience measure to evaluate the tool by applying a questionnaire-oriented approach. We discussed the applicability of our tool by including it as a core component of two different applications: 1) a contextaware recommender system for IoT configuration across layers; and 2) a tool for automatically translating an SLA from JSON to a smart contract, deploying it on different peer nodes that represent the contractual parties. The smart contract is able to monitor the created SLA using Blockchain technology. These two applications are utilized within our proposed SLA management framework for IoT. Furthermore, we propose a greedy heuristic algorithm to decentralize workflow activities of an IoT application across Edge and Cloud resources to enhance response time, cost, energy consumption and network usage. We evaluated the efficiency of our proposed approach using iFogSim simulator. The performance analysis shows that the proposed algorithm minimized cost, execution time, networking, and Cloud energy consumption compared to Cloud-only and edge-ward placement approaches

Adaptive monitoring and control framework in Application Service Management environment

The economics of data centres and cloud computing services have pushed hardware and software requirements to the limits, leaving only very small performance overhead before systems get into saturation. For Application Service Management–ASM, this carries the growing risk of impacting the execution times of various processes. In order to deliver a stable service at times of great demand for computational power, enterprise data centres and cloud providers must implement fast and robust control mechanisms that are capable of adapting to changing operating conditions while satisfying service–level agreements. In ASM practice, there are normally two methods for dealing with increased load, namely increasing computational power or releasing load. The first approach typically involves allocating additional machines, which must be available, waiting idle, to deal with high demand situations. The second approach is implemented by terminating incoming actions that are less important to new activity demand patterns, throttling, or rescheduling jobs. Although most modern cloud platforms, or operating systems, do not allow adaptive/automatic termination of processes, tasks or actions, it is administrators’ common practice to manually end, or stop, tasks or actions at any level of the system, such as at the level of a node, function, or process, or kill a long session that is executing on a database server. In this context, adaptive control of actions termination remains a significantly underutilised subject of Application Service Management and deserves further consideration. For example, this approach may be eminently suitable for systems with harsh execution time Service Level Agreements, such as real–time systems, or systems running under conditions of hard pressure on power supplies, systems running under variable priority, or constraints set up by the green computing paradigm. Along this line of work, the thesis investigates the potential of dimension relevance and metrics signals decomposition as methods that would enable more efficient action termination. These methods are integrated in adaptive control emulators and actuators powered by neural networks that are used to adjust the operation of the system to better conditions in environments with established goals seen from both system performance and economics perspectives. The behaviour of the proposed control framework is evaluated using complex load and service agreements scenarios of systems compatible with the requirements of on–premises, elastic compute cloud deployments, server–less computing, and micro–services architectures