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Modeling Big Data Systems by Extending the Palladio Component Model

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dc.contributor.authorKroß, Johannes
dc.contributor.authorBrunnert, Andreas
dc.contributor.authorKrcmar, Helmut
dc.date.accessioned2023-03-13T10:09:53Z
dc.date.available2023-03-13T10:09:53Z
dc.date.issued2015
dc.description.abstractThe growing availability of big data has induced new storing and processing techniques implemented in big data systems such as Apache Hadoop or Apache Spark. With increased implementations of these systems in organizations, simultaneously, the requirements regarding performance qualities such as response time, throughput, and resource utilization increase to create added value. Guaranteeing these performance requirements as well as efficiently planning needed capacities in advance is an enormous challenge. Performance models such as the Palladio component model (PCM) allow for addressing such problems. Therefore, we propose a metamodel extension for PCM to be able to model typical characteristics of big data systems. The extension consists of two parts. First, the meta-model is extended to support parallel computing by forking an operation multiple times on a computer cluster as intended by the single instruction, multiple data (SIMD) architecture. Second, modeling of computer clusters is integrated into the meta-model so operations can be properly scheduled on contained computing nodes.en
dc.identifier.pissn0720-8928
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/40768
dc.language.isoen
dc.publisherGeselllschaft für Informatik e.V.
dc.relation.ispartofSoftwaretechnik-Trends Band 35, Heft 3
dc.subjectPalladio Component Model
dc.subjectPerformance Model
dc.subjectBig Data
dc.titleModeling Big Data Systems by Extending the Palladio Component Modelen
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

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Softwaretechnik-Trends 35(3) - 2015