Towards Model-Driven Provisioning, Deployment, Monitoring, and Adaptation of Multi-cloud Systems

Ferry, Nicolas; Rossini, Alessandro; Chauvel, Franck; Morin, Brice; Solberg, Arnor

doi:10.1109/cloud.2013.133

Cited by 146 publications

(76 citation statements)

References 15 publications

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“…Moreover, MDE can also be used at runtime to maintain a model of the running system. The interest of MDE is demonstrated in several research areas, as for context-aware pervasive systems [18], [19], runtime adaptation [20], or multi-cloud systems management [21]. Concerning the multiscale vision of complex systems, a multiscale UML profile for the deployment of complex systems is proposed in [22].…”

Section: Related Workmentioning

confidence: 99%

MuSCa: A Multiscale Characterization Framework for Complex Distributed Systems

Rottenberg¹,

Leriche²,

Taconet³

et al. 2014

Annals of Computer Science and Information Systems

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Abstract-Nowadays, complex systems are distributed over several levels of Information and Communications Technology (ICT) infrastructures. They may involve very small devices such as sensors and RFID, but also powerful systems such as Cloud computers and knowledge bases, as well as intermediate devices such as smartphones and personal computers. These systems are sometimes referred to as multiscale systems. The word "multiscale" may qualify various distributed systems according to different viewpoints such as their geographic dispersion, the networks they are deployed on, or their users' organizations. For one entity of the multiscale system, communication technologies, non-functional properties (for persistence or security purpose) or architectures to be favored may vary from one scale to another. Moreover, ad hoc architecture of such complex systems are costly and non-sustainable. In this paper, we propose a scaleawareness framework, called MuSCa. This framework includes a characterization process based on the concepts of viewpoints, dimensions and scales. These concepts constitute the core of a dedicated metamodel. The proposed framework allows multiscale software designers to share a taxonomy for qualifying their own system. At system design time, the result of such a qualification is a model from which the framework produces scale-awareness artifacts. As an illustration of this model-driven approach, we show how multiscale probes are generated to provide multiscale components with an embedded scale-awareness ability.

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Section: Related Workmentioning

confidence: 99%

MuSCa: A Multiscale Characterization Framework for Complex Distributed Systems

Rottenberg¹,

Leriche²,

Taconet³

et al. 2014

Annals of Computer Science and Information Systems

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“…CAMEL integrates and extends existing DSLs, including Cloud Modelling Language (CloudML) [8,9], Saloon [14,15], and the Organisation part of CERIF [16], for specifying multiple aspects of multi-Cloud applications, such as provisioning, deployment, providers, organisations, users, and roles. Moreover, CAMEL adds DSLs for specifying aspects such as metrics, requirements, goals, scalability rules [17,18], security controls, execution contexts, execution histories, etc.…”

Section: Related Workmentioning

confidence: 99%

“…Deployment models are specified using CloudML. CloudML [8,9] consists of: (i) a domain-specific language (DSL) for specifying the provisioning and deployment of multi-Cloud applications; and (ii) a models@run-time environment for enacting the provisioning, deployment, and adaptation of these applications. While the CloudML language is part of MODACloudML, the models@runtime environment is integrated as part of the MODAClouds IDE.…”

Section: Cpim and Cpsm Modelsmentioning

confidence: 99%

The MODAClouds Model-Driven Development

Ferry

Almeida

Solberg

2016

Model-Driven Development and Operation of Multi-Cloud Applications

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The Cloud computing market encompasses an ever-growing number of providers offering a multitude of infrastructure-as-a-service (IaaS) and platform-as-a-service (PaaS) solutions. In order to exploit the peculiarities of each Cloud solution as well as to optimize performances, availability, and cost, an emergent need is to run and manage multi-Cloud applications [1] (i.e., applications that can execute on multiple Cloud infrastructures and platforms). However, current stacks, libraries and frameworks lack in software engineering methodologies and tools to design, deploy and maintain multi-Cloud systems as stated in the CORDIS reports on Cloud computing [2,3], "whilst a distributed data environment (IaaS) cannot be easily moved to any platform provider (PaaS) […], it is also almost impossible to move a service/image/environment between providers on the same level."Model-Driven Development (MDD) [4] techniques are particularly useful to address these challenges. They allow shifting the paradigm from code-centric to model-centric. Models are thus the main artefacts of the development process and enable developers to work at a high level of abstraction, focusing on Cloud concerns rather than implementation details. Model transformations help automating the work of going from abstract concepts to implementation. This approach, which is commonly summarized as "model once, generate anywhere", is thus particularly relevant when it comes to design and management of applications across multiple Clouds, N. Ferry · A. Solberg (B)

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“…In addition, there is a lack of a systematic engineering process and tools supported by reusable architectural artifacts [45]. The authors Nicolas Ferry et al [46] proposed Cloud Modeling language (CloudML) explain that model driven techniques and methods facilitating the specification of provisioning and deployment concerns of multi cloud systems , this will enables the continues evolution of system between design time and run time activities. Argue model driven is suitable for developing complex systems.…”

Section: Data Filtering Andanalysis (Extraction and Classification)mentioning

confidence: 99%

Model-Driven Architecture for Cloud Applications Development, A survey

Eldein¹,

Ammar²

2015

IJCATR

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Model Driven Architecture and Cloud computing are among the most important paradigms in software service engineering now a days. As cloud computing continues to gain more activities, more issues and challenges for many systems with its dynamic usage are introduced. Model Driven Architecture (MDA) approach for development and maintenance becomes an evident choice for ensuring software solutions that are robust, flexible and agile for developing applications. This paper aims to survey and analyze the research issues and challenges that have been emerging in cloud computing applications with a focus on using Model Driven architecture (MDA) development. We discuss the open research issues and highlight future research problems.

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Towards Model-Driven Provisioning, Deployment, Monitoring, and Adaptation of Multi-cloud Systems

Cited by 146 publications

References 15 publications

MuSCa: A Multiscale Characterization Framework for Complex Distributed Systems

MuSCa: A Multiscale Characterization Framework for Complex Distributed Systems

The MODAClouds Model-Driven Development

Model-Driven Architecture for Cloud Applications Development, A survey

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