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Please use this identifier to cite or link to this item: https://doi.org/10.21256/zhaw-3337
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dc.contributor.authorBenz, Konstantin-
dc.contributor.authorBohnert, Thomas M.-
dc.date.accessioned2019-03-29T07:16:33Z-
dc.date.available2019-03-29T07:16:33Z-
dc.date.issued2015-
dc.identifier.issn1877-0509de_CH
dc.identifier.urihttps://digitalcollection.zhaw.ch/handle/11475/16402-
dc.description.abstractThe main benefit of cloud computing lies in the elasticity of virtual resources that are provided to end users. Cloud users do not have to pay fixed hardware costs and are charged for consumption of computing resources only. While this might be an improvement for software developers who use the cloud, application users and consumers might rather be interested in paying for application performance than resource consumption. However there is little effort on providing elasticity based on performance goals instead of resource consumption. In this paper an autoscaling method is presented which aims at providing increased application performance as it is demanded by consumers. Elastic scaling is based on “statistical process monitoring and control” and “Western Electric rules”. By demonstrating the architecture of the autoscaling method and providing performance measurements gathered in an OpenStack cloud environment, we show how the injection of aspect-oriented code into cloud applications allows for improving application performance by automatically adapting the underlying virtual environment to pre-defined performance goals. The effectiveness of the autoscaling method is verified by an experiment with a test program which shows that the program executes in only half of the time which is required if no autoscaling capabilities are provided.de_CH
dc.language.isoende_CH
dc.publisherElsevierde_CH
dc.relation.ispartofProcedia Computer Sciencede_CH
dc.rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/de_CH
dc.subjectCloud computingde_CH
dc.subjectAutoscalingde_CH
dc.subjectVirtualizationde_CH
dc.subjectElasticityde_CH
dc.subjectScalabilityde_CH
dc.subjectAvailabilityde_CH
dc.subjectReliabilityde_CH
dc.subjectPerformancede_CH
dc.subjectWestern Electric rulede_CH
dc.subjectStatistical process controlde_CH
dc.subjectAspect-oriented codede_CH
dc.subject.ddc004: Informatikde_CH
dc.titleElastic scaling of cloud application performance based on Western Electric rules by injection of aspect-oriented codede_CH
dc.typeBeitrag in wissenschaftlicher Zeitschriftde_CH
dcterms.typeTextde_CH
zhaw.departementSchool of Engineeringde_CH
zhaw.organisationalunitInstitut für Informatik (InIT)de_CH
dc.identifier.doi10.21256/zhaw-3337-
dc.identifier.doi10.1016/j.procs.2015.09.193de_CH
zhaw.funding.euNode_CH
zhaw.originated.zhawYesde_CH
zhaw.pages.end205de_CH
zhaw.pages.start198de_CH
zhaw.publication.statuspublishedVersionde_CH
zhaw.volume61de_CH
zhaw.publication.reviewPeer review (Publikation)de_CH
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Benz, K., & Bohnert, T. M. (2015). Elastic scaling of cloud application performance based on Western Electric rules by injection of aspect-oriented code. Procedia Computer Science, 61, 198–205. https://doi.org/10.21256/zhaw-3337
Benz, K. and Bohnert, T.M. (2015) ‘Elastic scaling of cloud application performance based on Western Electric rules by injection of aspect-oriented code’, Procedia Computer Science, 61, pp. 198–205. Available at: https://doi.org/10.21256/zhaw-3337.
K. Benz and T. M. Bohnert, “Elastic scaling of cloud application performance based on Western Electric rules by injection of aspect-oriented code,” Procedia Computer Science, vol. 61, pp. 198–205, 2015, doi: 10.21256/zhaw-3337.
BENZ, Konstantin und Thomas M. BOHNERT, 2015. Elastic scaling of cloud application performance based on Western Electric rules by injection of aspect-oriented code. Procedia Computer Science. 2015. Bd. 61, S. 198–205. DOI 10.21256/zhaw-3337
Benz, Konstantin, and Thomas M. Bohnert. 2015. “Elastic Scaling of Cloud Application Performance Based on Western Electric Rules by Injection of Aspect-Oriented Code.” Procedia Computer Science 61: 198–205. https://doi.org/10.21256/zhaw-3337.
Benz, Konstantin, and Thomas M. Bohnert. “Elastic Scaling of Cloud Application Performance Based on Western Electric Rules by Injection of Aspect-Oriented Code.” Procedia Computer Science, vol. 61, 2015, pp. 198–205, https://doi.org/10.21256/zhaw-3337.


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