[{"language":[{"iso":"eng"}],"author":[{"last_name":"Püschel","first_name":"Tim","full_name":"Püschel, Tim"},{"last_name":"Schryen","first_name":"Guido","full_name":"Schryen, Guido","id":"72850"},{"full_name":"Hristova, Diana","first_name":"Diana","last_name":"Hristova"},{"last_name":"Neumann","first_name":"Dirk","full_name":"Neumann, Dirk"}],"year":"2015","title":"Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-probabilistic Uncertainty","intvolume":"       244","date_updated":"2022-01-06T07:02:30Z","date_created":"2018-11-14T15:40:13Z","file":[{"file_id":"6036","content_type":"application/pdf","file_name":"ELSEVIER_JOURNAL_VERSION.pdf","file_size":1270024,"access_level":"open_access","relation":"main_file","date_updated":"2018-12-13T15:09:12Z","date_created":"2018-12-07T11:44:10Z","creator":"hsiemes"}],"department":[{"_id":"277"}],"keyword":["admission control","informational uncertainty","revenue management","cloud computing"],"type":"journal_article","issue":"2","publication":"European Journal of Operational Research","extern":"1","abstract":[{"text":"Cloud computing promises the flexible delivery of computing services in a pay-as-you-go manner. It allows customers to easily scale their infrastructure and save on the overall cost of operation. However Cloud service offerings can only thrive if customers are satisfied with service performance. Allow-ing instantaneous access and flexible scaling while maintaining the service levels and offering competitive prices poses a significant challenge to Cloud Computing providers. Furthermore services will remain available in the long run only if this business generates a stable revenue stream. To address these challenges we introduce novel policy-based service admission control mod-els that aim at maximizing the revenue of Cloud providers while taking in-formational uncertainty regarding resource requirements into account. Our evaluation shows that policy-based approaches statistically significantly out-perform first come first serve approaches, which are still state of the art. Furthermore the results give insights in how and to what extent uncertainty has a negative impact on revenue.","lang":"eng"}],"publisher":"Elsevier","_id":"5679","page":"637-647","volume":244,"user_id":"61579","ddc":["000"],"status":"public","has_accepted_license":"1","oa":"1","citation":{"short":"T. Püschel, G. Schryen, D. Hristova, D. Neumann, European Journal of Operational Research 244 (2015) 637–647.","chicago":"Püschel, Tim, Guido Schryen, Diana Hristova, and Dirk Neumann. “Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-Probabilistic Uncertainty.” <i>European Journal of Operational Research</i> 244, no. 2 (2015): 637–47.","ieee":"T. Püschel, G. Schryen, D. Hristova, and D. Neumann, “Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-probabilistic Uncertainty,” <i>European Journal of Operational Research</i>, vol. 244, no. 2, pp. 637–647, 2015.","apa":"Püschel, T., Schryen, G., Hristova, D., &#38; Neumann, D. (2015). Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-probabilistic Uncertainty. <i>European Journal of Operational Research</i>, <i>244</i>(2), 637–647.","bibtex":"@article{Püschel_Schryen_Hristova_Neumann_2015, title={Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-probabilistic Uncertainty}, volume={244}, number={2}, journal={European Journal of Operational Research}, publisher={Elsevier}, author={Püschel, Tim and Schryen, Guido and Hristova, Diana and Neumann, Dirk}, year={2015}, pages={637–647} }","ama":"Püschel T, Schryen G, Hristova D, Neumann D. Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-probabilistic Uncertainty. <i>European Journal of Operational Research</i>. 2015;244(2):637-647.","mla":"Püschel, Tim, et al. “Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-Probabilistic Uncertainty.” <i>European Journal of Operational Research</i>, vol. 244, no. 2, Elsevier, 2015, pp. 637–47."},"file_date_updated":"2018-12-13T15:09:12Z"}]