A Reference Architecture for Cloud Service Offers

Gudenkauf, Stefan; Josefiok, Mirco; Göring, André; Norkus, Oliver

doi:10.1109/edoc.2013.33

Cited by 9 publications

(8 citation statements)

References 10 publications

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“…FBC was realized by the University of Oldenburg, OFFIS (associated institute of the University Oldenburg) and acatech (German nation Academy of science and engineering) and founded by the German federal ministry for economic affairs and energy. In this project, preliminary and basic work was realized and noted the continued need for work on BI cloud [50,51]. The University of Oldenburg and OFFIS are drivers of RABIC.…”

Section: Discussionmentioning

confidence: 99%

RABIC: A Reference Architecture for Business Intelligence in the Cloud

Norkus¹,

Sauer²

2016

JCC

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Classical Business Intelligence systems are based on common database management systems. The use of such classical, nonpolitical BI systems is not always the best solution. The incorporation of cloud computing technology offers great potential. Therefore, the combination of business intelligence and cloud computing is discussed more and more in science and industry with first products being already available on the market but so far no widespread use has been established. On the one hand, there are less scientifically based progress reports; on the other hand, there is an uncertainty and skepticism. Basic questions regarding the enterprise and software architecture are not yet clear. The absence of standards and transparency promotes skepticism and incomprehension. A lack of comparison and assessment models for BI cloud services and BI cloud systems fueled uncertainty. RABIC, the integrated reference architecture for business intelligence in the cloud, improves this situation by supporting the standardization, increase the transparency and abolish the skepticism. The measures to receive these objectives are to make BI cloud services in a uniform way describable and comparable and to make BI cloud systems assessable, comparable, describable and easier implementable. The vehicles as the integral constituents of the reference architecture are a taxonomy for BI cloud services and an architectural framework for BI cloud systems. This article presents an overview of the reference architecture.

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Section: Discussionmentioning

confidence: 99%

RABIC: A Reference Architecture for Business Intelligence in the Cloud

Norkus¹,

Sauer²

2016

JCC

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“…• Step 1: A pair of taxonomies from Figure 1 that have some common topic(s) (which will be used as a merging point) is selected each time. For example, taxonomies in [20] and [26] have cloud service pricing and pricing models, respectively, as a common topic. • Step 2: Any redundant and inconsistent topics between both taxonomies from step 1 were identified.…”

Section: Refinementmentioning

confidence: 99%

“…• Step 2: Any redundant and inconsistent topics between both taxonomies from step 1 were identified. For example, subscription in [20] is redundant with subscription in [26]. • Step 3: All redundant topics if there is any, except the one to be used as merging point(s), in both taxonomies are removed to retain the topic's uniqueness.…”

Section: Refinementmentioning

confidence: 99%

Infrastructure-as-a-Service Ontology for Consumer-Centric Assessment

Banditwattanawong,

Masdisornchote

2023

Adv. sci. technol. eng. syst. j.

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In the context of adopting cloud Infrastructure-as-a-Service (IaaS), prospective consumers need to consider a wide array of both business and technical factors associated with the service. The development of an intelligent tool to aid in the assessment of IaaS offerings is highly desirable. However, the creation of such a tool requires a robust foundation of domain knowledge. Thus, the focus of this paper is to introduce an ontology specifically designed to characterize IaaSs from the consumer's perspective, enabling informed decision-making. The ontology additionally serves two purposes of other relevant parties besides the consumers. Firstly, it empowers IaaS providers to better tailor their services to align with consumer expectations, thereby enhancing their competitiveness. Additionally, IaaS partners can play a pivotal role in supporting both consumers and providers by understanding the protocol outlined in the ontology that governs interactions between the two parties. By applying principles of ontological engineering, this study meticulously examined the various topics related to IaaS as delineated in existing cloud taxonomies. These topics were subsequently transformed into a standardized representation and seamlessly integrated through a binary integration approach. This process resulted in the creation of a comprehensive and cohesive ontology that maintains semantic consistency. Leveraging Protégé, this study successfully constructed the resultant ontology, comprising a total of 340 distinct classes. The study evaluated the syntactic, semantic, and practical aspects of the ontology against a worldwide prominent IaaS. The results showed that the proposed ontology was syntactically and semantically consistent. Furthermore, the ontology successfully enabled not only the assessment of a real leading IaaS but also queries to support automation tool development.

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“…Finally, the remaining two decisions (Select Cloud Vendor and Define Resource Location) are concerned with the evaluation of the reputation of the cloud provider in the manner discussed e.g. in [12], and of the physical location of the migrated data for regulatory compliance purposes [10] (Select Cloud Vendor and Define Resource Location, respectively).…”

Section: Knowledge Basementioning

confidence: 99%

“…Similarly, in [20], a resolution engine is presented that matches user-provided criteria with available offerings from a cloud service marketplace in order to identify suitable business-level offerings. In [12], the authors discuss a feature-based model for the description of service offerings that can be used for decision making towards offering selection. These works can be used as the basis for the implementation of a decision support system around CloudDSF.…”

Section: Related Workmentioning

confidence: 99%

CloudDSF – The Cloud Decision Support Framework for Application Migration

Andrikopoulos

Darsow

Karastoyanova

et al. 2014

Advanced Information Systems Engineering

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International audienceMigrating existing applications to cloud solutions is a multi-dimensional problem that spans beyond technical issues and into the financial, security and organizational domains. The existing works in the field form a picture of a maturing but still incomplete research area, requiring the introduction of comprehensive solutions for the migration of enterprise systems and applications to cloud solutions. As part of this effort, in this work we focus on supporting decision makers in evaluating the need for migration, and guiding them along the decisions that need to be made before the actual migration process. For this purpose we build on existing work to provide an elaborated decision support framework that is available as a Web application. We discuss the evaluation of the framework by experts, identify its deficiencies and outline our future steps. {keywordsApplication migration, decision support, decision visualization

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A Reference Architecture for Cloud Service Offers

Cited by 9 publications

References 10 publications

RABIC: A Reference Architecture for Business Intelligence in the Cloud

RABIC: A Reference Architecture for Business Intelligence in the Cloud

Infrastructure-as-a-Service Ontology for Consumer-Centric Assessment

CloudDSF – The Cloud Decision Support Framework for Application Migration

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