Adaptive Application Performance Management for Big Data Stream Processing
dc.contributor.author | Eichelberger, Holger | |
dc.contributor.author | Qin, Cui | |
dc.contributor.author | Schmid, Klaus | |
dc.contributor.author | Niederée, Claudia | |
dc.date.accessioned | 2023-03-13T10:09:53Z | |
dc.date.available | 2023-03-13T10:09:53Z | |
dc.date.issued | 2015 | |
dc.description.abstract | Big data applications with their high-volume and dynamically changing data streams impose new challenges to application performance management. Efficient and effective solutions must balance performance versus result precision and cope with dramatic changes in real-time load and needs without overprovisioning resources. Moreover, a developer should not be burdened too much with addressing performance management issues, so he can focus on the functional perspective of the system For addressing these challenges, we present a novel comprehensive approach, which combines software configuration, model-based development, application performance management and runtime adaptation. | en |
dc.identifier.pissn | 0720-8928 | |
dc.identifier.uri | https://dl.gi.de/handle/20.500.12116/40770 | |
dc.language.iso | en | |
dc.publisher | Geselllschaft für Informatik e.V. | |
dc.relation.ispartof | Softwaretechnik-Trends Band 35, Heft 3 | |
dc.subject | Adaptive performance management | |
dc.subject | resource adaptation | |
dc.subject | stream processing | |
dc.subject | algorithm families | |
dc.subject | Big data | |
dc.subject | QualiMaster. | |
dc.title | Adaptive Application Performance Management for Big Data Stream Processing | en |
dc.type | Text/Journal Article | |
gi.citation.publisherPlace | Bonn | |
gi.conference.sessiontitle | Sonderteil: Proceedings of the Symposium on Software Performance (SSP) 2015, 4. - 6. November 2015, Munich, Germany |
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