SRL: A Scalability Rule Language for Multi-cloud Environments

Kritikos, Kyriakos; Domaschka, Jörg; Rossini, Alessandro

doi:10.1109/cloudcom.2014.170

Cited by 36 publications

(26 citation statements)

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“…Also, it is assumed that the deployed service is scalable by design. In [29], a language for scalability rules for multi-cloud environments is proposed as a part of Cloud Application Modeling and Execution Language (CAMEL). It provides high expressiveness in terms of event patterns, performance metrics and scaling actions, at the cost of a complex form.…”

Section: State Of the Artmentioning

confidence: 99%

Self-scalable services in service oriented software for cost-effective data farming

Król

Kitowski

2016

Future Generation Computer Systems

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Section: State Of the Artmentioning

confidence: 99%

Self-scalable services in service oriented software for cost-effective data farming

Król

Kitowski

2016

Future Generation Computer Systems

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“…A DSL language, named Scalability Rule Language (SRL), has been proposed in [Kritikos 2014] for specifying scalability rules through defining event patterns of multi-Cloud application as well as scaling actions. SRL has been inspired by OWL-Q language for specifying QoS metrics as well as the Esper Processing Language (EPL) for specifying event patterns.…”

Section: Elasticity Strategies Descriptionmentioning

confidence: 99%

“…• Granularity : Even though some of the studied approaches , Copil 2013, Kritikos 2014 have tried specifying QoS requirements (e.g, the defined thresholds for QoS metrics) at different granularity levels, none of them have considered the request level, i.e., distinguishing between requests requirements. In fact, all of them have assumed that QoS related requirements are the same for all requests.…”

Section: Synthesis Of Related Workmentioning

confidence: 99%

Description and Evaluation of Elasticity Strategies for Business Processes in the Cloud

Bhiri

Tata

2016

2016 IEEE International Conference on Services Computing (SCC)

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Titre : Description et évaluation de stratégies d'élasticité des processus métiers dans le Cloud Mots clés : Applications à base de services, Stratégies d'élasticité, Evaluation, Modèle d'élasticité, Cloud Computing. Résumé : De nos jours, de plus en plus d'entreprises migrent leurs applications à base de services (AbSs) vers le Cloud. L'élasticité du Cloud Computing est la caractéristique principale derrière ce phénomène de migration. Le principe d'élasticité a attiré beaucoup d'attention ces dernières années comme une tâche pivot qui permet d'assurer un bon compromis entre les Qualités de service désirées et les coûts opérationnels des AbSs. Toutefois, le contrôle d'élasticité des AbSs et la définition des stratégies d'élasticité non-triviales sont encore des tâches difficiles à réaliser. La difficulté de ces tâches est de plus accentuée avec l'absence d'un langage unifié pour exprimer ces stratégies et un moyen pour les évaluer et les valider avant de les utiliser dans un environnement Cloud réel. Dans notre travail, nous nous intéressons à la définition et l'évaluation des stratégies d'élasticité des applications à base de services dans le Cloud.

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“…Enhancing the role of the cloud broker as guarantor of quality assurance was the premise behind the EU FP7 BrokerCloud project , which investigated methods and mechanisms for continuous quality assurance and optimization of brokered software services in the cloud. The project demonstrated a brokerage platform which could validate and test software services prior to uploading ( certification at onboarding ) , manage the service lifecycle from creation to decommissioning ( lifecycle governance ) , regulate the performance and availability of services ( monitoring and adaptation ) and recommend alternative service bundles, according to customer preferences ( preference‐based arbitrage ) . The current article describes the novel verification and testing approach that was developed to assure functional quality and substitutability, as part of a service certification strategy.…”

Section: Introductionmentioning

confidence: 99%

A verified and optimized Stream X‐Machine testing method, with application to cloud service certification

Simons

Lefticaru

2020

Software Testing Verif & Rel

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Summary The Stream X‐Machine (SXM) testing method provides strong and repeatable guarantees of functional correctness, up to a specification. These qualities make the method attractive for software certification, especially in the domain of brokered cloud services, where arbitrage seeks to substitute functionally equivalent services from alternative providers. However, practical obstacles include the difficulty in providing a correct specification, the translation of abstract paths into feasible concrete tests and the large size of generated test suites. We describe a novel SXM verification and testing method, which automatically checks specifications for completeness and determinism, prior to generating complete test suites with full grounding information. Three optimization steps achieve up to a 10‐fold reduction in the size of the test suite, removing infeasible and redundant tests. The method is backed by a set of tools to validate and verify the SXM specification, generate technology‐agnostic test suites and ground these in SOAP, REST or rich‐client service implementations. The method was initially validated using seven specifications, three cloud platforms and five grounding strategies.

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SRL: A Scalability Rule Language for Multi-cloud Environments

Cited by 36 publications

References 1 publication

Self-scalable services in service oriented software for cost-effective data farming

Self-scalable services in service oriented software for cost-effective data farming

Description and Evaluation of Elasticity Strategies for Business Processes in the Cloud

A verified and optimized Stream X‐Machine testing method, with application to cloud service certification

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