CloudML: An Integrated Language for Resource, Service and Request Description for D-Clouds

Gonçalves, Glauco Estácio; Endo, Patrícia Takako; Santos, Marcelo; Sadok, Djamel; Kelner, Judith; Melander, Bob; Mångs, Jan-Erik

doi:10.1109/cloudcom.2011.60

Cited by 28 publications

(16 citation statements)

References 8 publications

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“…Por fim, o Puppet é uma ferramenta que automatiza os processos administrativos, e.g., instalações de pacotes e atualização das configurações dos servidores [60]. [43], CloudML [26], OCCI [53] Verificando a Tabela 7, percebe-se exemplos de agentes autônomos baseados em CLI, como a ferramenta gsutil Tool do Google e a interface da linha de comando da Amazon AWS. A gsutil é uma ferramenta desenvolvida pela empresa Google e fornece meios dos usuários acessarem a Goolgle Cloud Storage através de CLI [31].…”

Section: Classificação De Mecanismos E Soluçõesunclassified

Uma taxonomia para corretagem de nuvens IaaS baseada na migração de infraestruturas virtuais

Cardoso

Miers

Koslovski

2017

RBCA

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Resumo: A computação em nuvem propõe um modelo no qual o usuário tem a ideia de recursos ilimitados, que podem ser reservados dinamicamente, pagando somente o que for consumido. Esse modelo de tarifação é conhecido como pay-as-you-go. Estes e outros fatores, levaram a uma ampla adoção dos serviços oferecidos pelas nuvens computacionais por parte dos usuários. Porém, ao migrarem aplicações para a nuvem, os usuários se deparam com uma quantidade expressiva de provedores, recursos, corretores e serviços oferecidos. Através da análise de material coletado em uma pesquisa referenciada, este trabalho propõe uma taxonomia para a classificação de atores relacionados com a corretagem de nuvens de acordo com as suas principais características. Nas referências são citados diversos recursos e tipos de serviços, porém este trabalho mantém o foco na migração de infraestruturas virtuais entre provedores de Infrastructure-as-a-Service (IaaS). Palavras-chave: Corretagem, IaaS, Nuvens, Corretores, Migração, InteroperabilidadeAbstract: Cloud computing offers a model in which the user has the idea of unlimited resources. Allied with this idea, cloud computing also provides another advantage that allows the user to pay only what is consumed, this model is also known as pay as you go. These and other factors led to a broad adoption of services offered by cloud computing. However, when the users migrates their applications to the cloud, they faced several possibilities of providers, resources, brokers, and services. Through a analysis of articles and books relevant to the subject, we propose a taxonomy in order to classify cloud brokers according to their main features. The references mention several features, but this work keeps focused in migration of virtual infrastructures between Infrastructureas-a-Service (IaaS) providers.

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Section: Classificação De Mecanismos E Soluçõesunclassified

Uma taxonomia para corretagem de nuvens IaaS baseada na migração de infraestruturas virtuais

Cardoso

Miers

Koslovski

2017

RBCA

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“…Other domain specific languages for the deployment of applications in the clouds have been proposed, e.g., the component based application model of [7], CloudML [13], and CloudMF [9]. All these approaches mainly aim at modeling the entities involved in the cloud and effective and efficient deployment engines are still to be developed for them.…”

Section: Related Workmentioning

confidence: 99%

“…The most popular approach in this specific context, is the one promoted by the DevOps community that aims at the automation of deployment starting from application-dependent deployment information. Modeling languages for deployment have been already proposed [9,13,19]. In this paper we take a complementary approach: we intend to investigate the integration of deployment within an existing modeling language, thus allowing for the reasoning about deployment at the application modeling level in a declarative way.…”

Section: Introductionmentioning

confidence: 99%

On the Integration of Automatic Deployment into the ABS Modeling Language

Gouw

Lienhardt

Mauro

et al. 2015

Service Oriented and Cloud Computing

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Abstract. In modern software systems, deployment is an integral and critical part of application development (see, e.g., the DevOps approach to software development). Nevertheless, deployment is usually overlooked at the modeling level, thus losing the possibility to perform deployment conscious decisions during the early stages of development. In this paper, we address the problem of promoting deployment as an integral part of modeling, by focusing on the Abstract Behavioral Specification (ABS) language used for the specification of models of systems composed of concurrent objects consuming resources provided by deployment components. We extend ABS with class annotations expressing the resource requirements of the objects of that class. Then we define a tool that, starting from a high-level declaration of the desired system, computes a model instance of such system that optimally distributes objects over available deployment components.

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“…The description of infrastructure-related cloud services and cloud resources is covered by CloudML-UFPE [30]. CloudML-UFPE proposes an XML-based approach to represent services offered by cloud providers.…”

Section: Cloudml-ufpementioning

confidence: 99%

“…Starting from the above-mentioned projects and their related work, we selected teo different approaches: Blueprint [43], CAML [8], CJoudMIG [27], CloudML [23], CloudML-UFPE 1 [30], H<JP!, MOCCA [39], MULTICLAPP [3 1], RESERVOIR-ML [20], and TOSCA [10]. For each selected approach, we provide a brief description and then categorize it according to both modeling language characteristics and cloud computing characteristics.…”

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confidence: 99%

Cloud Modeling Languages by Example

Bergmayr

Wimmer

Kappel

et al. 2014

2014 IEEE 7th International Conference on Service-Oriented Computing and Applications

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Abstract-Rece ntly, several proposals towards a cloud model· ing language have erneq;;cd. As they ad dress the diversity of cloud envimnments, il is not surprising that these modeling languages support different S(. 'Cfllll·ios. Using a by-example approach based on the sce nario of softw:uc migration, we demonstrate their represe ntational Cllpabilitics :md review them according to d!aracteristics common lo all modeling languages as weiJ as specific to the cloud computing donmin. We repor t on our findings an d present research guidelines for future efforts towards a better alignment of the different cloud modeling languages. I. I NTRODUCTIONCloud computing bas recently emerged as a new possibility how software can be made available to clients as a service. Hereby, software is hosted on a cloud environment [5] and consumable over the network by different clients. For software vendors, th. is is appealing because of low upfroot costs compared to a traditional on-premise solution as well as operational costs that scale with the provisioning and releasing of cloud resources, which are in turn offered as a service by cloud providers. Cloud service offerings range from low-level infrastructure elements, such as raw computing nodes, over higher level platforms, such as a Java execution environment on top of a cloud infrastructure, to ready-to-use software deployed on a cloud platform. Furthermore, software vendors are no longer forced to plan far ahead for resource provisioning [3] because the large-scale datacenters of today's cloud providers ensure that requested resources are available through their cloud environments. The risk of under-and over-provisioning of such resources is reduced by cloud environments due to their capabilities for elastic scalability on demand. Therefore, resources are not only provisioned as their demand increases but also released once their demand decreases (e.g. , number of user requests exceeds or falls below a defined threshold).Since cloud environments offer novel optimization opportunities (e.g., advanced scalable data persistence solutions), taking full advantage of the cloud requires that the software is prepared for such an environment However, in order to leverage the possibilities of a cloud environment, the software often needs to comply with certain restrictions that might hinder its functioning (e.g., statefuJ components in a highly scalable cloud environment). Several previous and ongoing European projects, notably REMICS [41] For each selected approach, we provide a brief description and then categorize it according to both modeling language characteristics and cloud computing characteristics. We do not claim that this set of cloud modeling language is complete and leave a systematic li terature review for future work. Rather, we foc us on the ex tensional perspective of the modeling languages by demonstrating the approaches in the setting of a cloud migration scenario. We have selected this scenario since it covers the wide spectrum of the software lifecycle. Finally, we c...

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CloudML: An Integrated Language for Resource, Service and Request Description for D-Clouds

Cited by 28 publications

References 8 publications

Uma taxonomia para corretagem de nuvens IaaS baseada na migração de infraestruturas virtuais

Uma taxonomia para corretagem de nuvens IaaS baseada na migração de infraestruturas virtuais

On the Integration of Automatic Deployment into the ABS Modeling Language

Cloud Modeling Languages by Example

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