Logo des Repositoriums
 

Analyzing Cost-Efficiency of Cloud Computing Applications with SimuLizar

dc.contributor.authorLehrig, V
dc.contributor.authorEikerling, Hendrik
dc.date.accessioned2023-03-13T10:09:55Z
dc.date.available2023-03-13T10:09:55Z
dc.date.issued2015
dc.description.abstractIn cloud computing, software applications are potentially able to use only the computing resources that are minimally needed for performant operation. Because cloud providers provision such resources on a pay-per-use basis, software architects are interested in analyzing the operational costs that accrue for such applications, allowing architects to optimize for cost-efficiency. Current analysis approaches like Palladio focus on traditional performance metrics but lack support for cost-efficiency metrics. Therefore, software architects have to inaccurately estimate operational costs of their applications, potentially leading to economically unusable applications. To tackle this problem, we integrated cost metrics into SimuLizar, a Palladio extension for analyzing cloud computing applications. Our integration allows architects to attach prices to computing resources used by software applications. In a proof-of-concept evaluation with a simple book shop, we show that our integration allows architects to analyze costs with high accuracy.en
dc.identifier.pissn0720-8928
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/40774
dc.language.isoen
dc.publisherGeselllschaft für Informatik e.V.
dc.relation.ispartofSoftwaretechnik-Trends Band 35, Heft 3
dc.subjectCommunication Networks; Distributed System; Cloud applications; Software Engineering; Metrics—Scalability; Elasticity; Efficiency
dc.titleAnalyzing Cost-Efficiency of Cloud Computing Applications with SimuLizaren
dc.typeText/Journal Article
gi.citation.publisherPlaceBonn
gi.conference.sessiontitleSonderteil: Proceedings of the Symposium on Software Performance (SSP) 2015, 4. - 6. November 2015, Munich, Germany

Dateien

Originalbündel
1 - 1 von 1
Vorschaubild nicht verfügbar
Name:
SSP_2015_paper_13.pdf
Größe:
288.13 KB
Format:
Adobe Portable Document Format