SALOON: a platform for selecting and configuring cloud environments

Quinton, Clément; Romero, Daniel; Duchien, Laurence

doi:10.1002/spe.2311

Cited by 28 publications

(32 citation statements)

References 33 publications

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“…Moreover, COAPS complies to the previous, non-enhanced version of the OCCI standard, hence it lacks of the resource state management and the conformance verification provided by the OCCIware tool chain and MoDMaCAO. SALOON (Quinton et al, 2016) is a model-driven multi-cloud configurator. It uses feature models to represent infrastructure and platform variability, as well as ontologies to describe the cloud applications requirements.…”

Section: Related Workmentioning

confidence: 99%

“…This heterogeneity of cloud provider interfaces makes it hard to migrate applications between different cloud providers or combine different offerings. To tackle this problem, three different strategies can be identified in the literature: using code libraries that provide a common Application Programming Interface (API) for the different cloud provider APIs, e.g., Apache jclouds 1 , 2 , or fog 3 , using techniques from model driven engineering (MDE) to decouple the cloud applications from the technical peculiarities of the different target platforms, e.g., OCCIware , and SALOON (Quinton et al, 2016), and the development of common standards, e.g., the Topology and Orchestration Specification for Cloud Applications (TOSCA) 4 , and the Open Cloud Com-1 http://www.jclouds.org 2 All URLs have been last retrieved on 01/03/2018. 3 http://fog.io 4 https://www.oasis-open.org/committees/TOSCA/ puting Interface (OCCI) (Nyrén et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Model-driven Configuration Management of Cloud Applications with OCCI

Korte

Challita

Zalila

et al. 2018

Proceedings of the 8th International Conference on Cloud Computing and Services Science

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Abstract:To tackle the cloud-provider lock-in, the Open Grid Forum (OGF) is developing the Open Cloud Computing Interface (OCCI), a standardized interface for managing any kind of cloud resources. Besides the OCCI Core model, which defines the basic modeling elements for cloud resources, the OGF also defines extensions that reflect the requirements of different cloud service levels, such as IaaS and PaaS. However, so far the OCCI PaaS extension is very coarse grained and lacks of supporting use cases and implementations. Especially, it does not define how the components of the application itself can be managed. In this paper, we present a model-driven framework that extends the OCCI PaaS extension and is able to use different configuration management tools to manage the whole lifecycle of cloud applications. We demonstrate the feasibility of the approach by presenting four different use cases and prototypical implementations for three different configuration management tools.

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Section: Related Workmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Model-driven Configuration Management of Cloud Applications with OCCI

Korte

Challita

Zalila

et al. 2018

Proceedings of the 8th International Conference on Cloud Computing and Services Science

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“…An acceptor will reply with the greatest id (rid ) that it has seen, the greatest id (rid r ) it has proposed, and the corresponding value (val r ), or NULL if it has not accepted any proposal as Phase 1B message. In the event that the received cid is smaller than rid r , the received prepare message will be disregarded (lines [18][19][20][21][22].…”

Section: Normal Operationmentioning

confidence: 99%

Adaptive trade‐off between consistency and performance in data replication

et al. 2016

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Summary Replication is widely adopted in modern Internet applications and distributed systems to improve the reliability and performance. Though maintaining the strong consistency among replicas can guarantee the correctness of application behaviors, however, it will affect the application performance at the same time because there is a well‐known trade‐off between consistency and performance. Many real‐world applications favoring performance often choose to enforce weak consistency. Although there has been some work on flexible configuration of consistency, most focuses on design or deployment time. As the system settings constantly change during runtime, the tuning of the consistency‐performance trade‐off needs to be handled dynamically. Failing to do that will cause either underestimation or overestimation of the consistency and performance that can be achieved. Existing work does not well support the dynamic tuning of the aforementioned trade‐off in runtime, which is mainly because of the lack of an appropriate quantitative model of consistency and performance. In this work, based on our previous effort on the quantitative model of consistency and latency, we design a replication protocol, CC‐Paxos, to achieve an adaptive trade‐off between consistency and performance according to application preferences and runtime information. By design, CC‐Paxos is not bound to any specific underlying data stores. We have implemented CC‐Paxos and applied it to MySQL databases. And real experiments both within a data center and across data centers show that CC‐Paxos not only can dynamically adjust the delivered consistency in return for ensured performance but also outperforms MySQL Cluster in the case of strong consistency guarantee. Copyright © 2016 John Wiley & Sons, Ltd.

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“…We do not want to emphasize one particular variability modeling approach (e.g., feature-based, decisionoriented, UML-based, or orthogonal variability models) but we use the general term variability model to describe any model of the variability of a software system. Such a model may be created using any approach that provides advanced modeling capabilities such as cardinalities and attributes [7,15] necessary in a dspl context to describe additional information like the number of instances of a feature or component at runtime. We also analyze the impact of evolution operations on the consistency of the dspl: the evolution of problem or solution space can lead to inconsistencies within the given space, between spaces, and with respect to rules for the runtime adaptation of the system.…”

Section: Introductionmentioning

confidence: 99%

Evolution in dynamic software product lines

Quinton

Rabiser

Vierhauser

et al. 2015

Proceedings of the 19th International Conference on Software Product Line

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In many domains systems need to run continuously and cannot be shut down for reconfiguration or maintenance tasks. Cyber-physical or cloud-based systems, for instance, thus often provide means to support their adaptation at runtime. The required flexibility and adaptability of systems suggests the application of Software Product Line (spl) principles to manage their variability and to support their reconfiguration. Specifically, Dynamic Software Product Lines (dspl) have been proposed to support the management and binding of variability at runtime. While spl evolution has been widely studied, it has so far not been investigated in detail in a dspl context. Variability models that are used in a dspl have to co-evolve and be kept consistent with the systems they represent to support reconfiguration even after changes to the systems at runtime. In this short paper we present a classification of the required operations for jointly evolving problem and solution space in a dspl. We analyze the impact of such operations on the consistency of a dspl and propose an approach to deal with the described issues. We describe a runtime monitoring system used in the domain of industrial automation software as an example of a dspl evolving at runtime to motivate and explain our work.

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SALOON: a platform for selecting and configuring cloud environments

Cited by 28 publications

References 33 publications

Model-driven Configuration Management of Cloud Applications with OCCI

Model-driven Configuration Management of Cloud Applications with OCCI

Adaptive trade‐off between consistency and performance in data replication

Evolution in dynamic software product lines

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