Adaptable Service Oriented Infrastructure Provisioning with Lightweight Containers Virtualization Technology

Modern computing infrastructures should enable realization of converged provisioning and governance operations on virtualized computing, storage and network resources used on behalf of users' workloads. These workloads must have ensured sufficient access to the resources to satisfy required QoS. This requires flexible platforms providing functionality for construction, activation and governance of Runtime Infrastructure which can be realized according to Service Oriented Infrastructure (SOI) paradigm. Implementation of the SOI management framework requires definition of flexible architecture and utilization of advanced software engineering and policy-based techniques. The paper presents an Adaptable SOI Provisioning Platform which supports adaptable SOI provisioning with lightweight virtualization, compliant with the structured process model suitable for construction, activation and governance of IT environments. The requirements, architecture and implementation of the platform are all discussed. Practical usage of the platform is presented on the basis of a complex case study for provisioning JEE middleware on top of the Solaris 10 lightweight virtualization platform

Virtual Cluster Management for Analysis of Geographically Distributed and Immovable Data

Thesis (Ph.D.) - Indiana University, Informatics and Computing, 2015Scenarios exist in the era of Big Data where computational analysis needs to utilize widely distributed and remote compute clusters, especially when the data sources are sensitive or extremely large, and thus unable to move. A large dataset in Malaysia could be ecologically sensitive, for instance, and unable to be moved outside the country boundaries. Controlling an analysis experiment in this virtual cluster setting can be difficult on multiple levels: with setup and control, with managing behavior of the virtual cluster, and with interoperability issues across the compute clusters. Further, datasets can be distributed among clusters, or even across data centers, so that it becomes critical to utilize data locality information to optimize the performance of data-intensive jobs. Finally, datasets are increasingly sensitive and tied to certain administrative boundaries, though once the data has been processed, the aggregated or statistical result can be shared across the boundaries. This dissertation addresses management and control of a widely distributed virtual cluster having sensitive or otherwise immovable data sets through a controller. The Virtual Cluster Controller (VCC) gives control back to the researcher. It creates virtual clusters across multiple cloud platforms. In recognition of sensitive data, it can establish a single network overlay over widely distributed clusters. We define a novel class of data, notably immovable data that we call "pinned data", where the data is treated as a first-class citizen instead of being moved to where needed. We draw from our earlier work with a hierarchical data processing model, Hierarchical MapReduce (HMR), to process geographically distributed data, some of which are pinned data. The applications implemented in HMR use extended MapReduce model where computations are expressed as three functions: Map, Reduce, and GlobalReduce. Further, by facilitating information sharing among resources, applications, and data, the overall performance is improved. Experimental results show that the overhead of VCC is minimum. The HMR outperforms traditional MapReduce model while processing a particular class of applications. The evaluations also show that information sharing between resources and application through the VCC shortens the hierarchical data processing time, as well satisfying the constraints on the pinned data

Contribución a la estimulación del uso de soluciones Cloud Computing: Diseño de un intermediador de servicios Cloud para fomentar el uso de ecosistemas distribuidos digitales confiables, interoperables y de acuerdo a la legalidad. Aplicación en entornos multi-cloud.

184 p.El objetivo del trabajo de investigación presentado en esta tesis es facilitar a los desarrolladores y operadores de aplicaciones desplegadas en múltiples Nubes el descubrimiento y la gestión de los diferentes servicios de Computación, soportando su reutilización y combinación, para generar una red de servicios interoperables, que cumplen con las leyes y cuyos acuerdos de nivel de servicio pueden ser evaluados de manera continua. Una de las contribuciones de esta tesis es el diseño y desarrollo de un bróker de servicios de Computación llamado ACSmI (Advanced Cloud Services meta-Intermediator). ACSmI permite evaluar el cumplimiento de los acuerdos de nivel de servicio incluyendo la legislación. ACSmI también proporciona una capa de abstracción intermedia para los servicios de Computación donde los desarrolladores pueden acceder fácilmente a un catálogo de servicios acreditados y compatibles con los requisitos no funcionales establecidos.Además, este trabajo de investigación propone la caracterización de las aplicaciones nativas multiNube y el concepto de "DevOps extendido" especialmente pensado para este tipo de aplicaciones. El concepto "DevOps extendido" pretende resolver algunos de los problemas actuales del diseño, desarrollo, implementación y adaptación de aplicaciones multiNube, proporcionando un enfoque DevOps novedoso y extendido para la adaptación de las prácticas actuales de DevOps al paradigma multiNube

Une architecture de cloud broker basée sur la sémantique pour l'optimisation de la satisfaction des utilisateurs

Cloud Computing is a dynamic new technology that has huge potentials in enterprises and markets. The dynamicity and the increasing complexity of Cloud architectures involve several management challenges. In this work, we are interested in Service Level Agreement (SLA) management. Actually, there is no standard to express Cloud SLA, so, providers describe their SLAs in different manner and different languages, which leaves the user puzzled about the choice of its Cloud provider. To overcome these problems, we introduce a Cloud Broker Architecture managing the SLA between providers and consumers. It aims to assist users in establishing and negotiating SLA contracts and to help them in finding the best provider that satisfies their service level expectations. Our broker SLA contracts are formalized as OWL ontologies as they allow hiding the heterogeneity in the distributed Cloud environment and enabling interoperability between Cloud actors. Besides, by combining our ontology with our proposed inference rules, we contribute to detect violations in the SLA contract assuring thereby the sustainability of the user satisfaction. Based on the requirements specified in the SLA contract, our Cloud Broker assists users in selecting the right provider using a multi attribute utility theory method. This method is based on utility functions representing the user satisfaction degree. To obtain accurate results, we have modelled both functional and non functional attributes utilities. We have used personalized utilities for each criterion under negotiation so that our cloud broker satisfies the best consumer requirements from functional and non functional point of viewLe Cloud Computing est un nouveau modèle économique hébergeant les applications de la technologie de l’information. Le passage au Cloud devient un enjeu important des entreprises pour des raisons économiques. La nature dynamique et la complexité croissante des architectures de Cloud impliquent plusieurs défis de gestion. Dans ce travail, nous nous intéressons à la gestion des contrats SLA. Vu le manque de standardisation, chaque fournisseur de service décrit les contrats SLA avec son propre langage, ce qui laisse l'utilisateur perplexe concernant le choix de son fournisseur de services. Dans ce travail, nous proposons une architecture de Cloud Broker permettant d’établir et de négocier les contrats SLA entre les fournisseurs et les consommateurs du Cloud. L’objectif de cette architecture est d’aider l’utilisateur à trouver le meilleur fournisseur en utilisant une méthode multi-critère. Cette méthode considère chaque critère comme une fonction d’utilité à intégrer dans une super-fonction d’utilité. Nous proposons d’illustrer chaque fonction d’utilité par une courbe spécifique à lui représentant bien le critère de choix. Nous essayons de cerner la plupart des critères qui contribuent dans le choix du meilleurs service et de les classer en critères fonctionnels et critères non fonctionnels. Les contrats SLA établit par notre broker sont formalisés sous forme d’ontologies qui permettent de masquer l'hétérogénéité et d’assurer l'interopérabilité entre les acteurs du Cloud. En outre, l’utilisation des règles d'inférence nous a permis de détecter les violations dans le contrat SLA établit et de garantir ainsi le respect de la satisfaction client dans le temp

Conformance Checking and Simulation-based Evolutionary Optimization for Deployment and Reconfiguration of Software in the Cloud

Many SaaS providers nowadays want to leverage the cloud's capabilities also for their existing applications, for example, to enable sound scalability and cost-effectiveness. This thesis provides the approach CloudMIG that supports SaaS providers to migrate those applications to IaaS and PaaS-based cloud environments. CloudMIG consists of a step-by-step process and focuses on two core components. (1) Restrictions imposed by specific cloud environments (so-called cloud environment constraints (CECs)), such as a limited file system access or forbidden method calls, can be validated by an automatic conformance checking approach. (2) A cloud deployment option (CDO) determines which cloud environment, cloud resource types, deployment architecture, and runtime reconfiguration rules for exploiting a cloud's elasticity should be used. The implied performance and costs can differ in orders of magnitude. CDOs can be automatically optimized with the help of our simulation-based genetic algorithm CDOXplorer. Extensive lab experiments and an experiment in an industrial context show CloudMIG's applicability and the excellent performance of its two core components

Towards Interoperable Research Infrastructures for Environmental and Earth Sciences

This open access book summarises the latest developments on data management in the EU H2020 ENVRIplus project, which brought together more than 20 environmental and Earth science research infrastructures into a single community. It provides readers with a systematic overview of the common challenges faced by research infrastructures and how a ‘reference model guided’ engineering approach can be used to achieve greater interoperability among such infrastructures in the environmental and earth sciences. The 20 contributions in this book are structured in 5 parts on the design, development, deployment, operation and use of research infrastructures. Part one provides an overview of the state of the art of research infrastructure and relevant e-Infrastructure technologies, part two discusses the reference model guided engineering approach, the third part presents the software and tools developed for common data management challenges, the fourth part demonstrates the software via several use cases, and the last part discusses the sustainability and future directions