[{"file":[{"access_level":"open_access","file_name":"ELSEVIER_JOURNAL_VERSION.pdf","date_created":"2018-12-07T11:44:10Z","relation":"main_file","date_updated":"2018-12-13T15:09:12Z","content_type":"application/pdf","file_id":"6036","creator":"hsiemes","file_size":1270024}],"author":[{"last_name":"Püschel","first_name":"Tim","full_name":"Püschel, Tim"},{"last_name":"Schryen","id":"72850","first_name":"Guido","full_name":"Schryen, Guido"},{"full_name":"Hristova, Diana","first_name":"Diana","last_name":"Hristova"},{"full_name":"Neumann, Dirk","first_name":"Dirk","last_name":"Neumann"}],"publisher":"Elsevier","file_date_updated":"2018-12-13T15:09:12Z","publication":"European Journal of Operational Research","keyword":["admission control","informational uncertainty","revenue management","cloud computing"],"has_accepted_license":"1","status":"public","date_created":"2018-11-14T15:40:13Z","volume":244,"abstract":[{"lang":"eng","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."}],"extern":"1","user_id":"61579","ddc":["000"],"citation":{"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,” European Journal of Operational Research, vol. 244, no. 2, pp. 637–647, 2015.","short":"T. Püschel, G. Schryen, D. Hristova, D. Neumann, European Journal of Operational Research 244 (2015) 637–647.","mla":"Püschel, Tim, et al. “Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-Probabilistic Uncertainty.” European Journal of Operational Research, vol. 244, no. 2, Elsevier, 2015, pp. 637–47.","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} }","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.” European Journal of Operational Research 244, no. 2 (2015): 637–47.","apa":"Püschel, T., Schryen, G., Hristova, D., & Neumann, D. (2015). Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-probabilistic Uncertainty. European Journal of Operational Research, 244(2), 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. European Journal of Operational Research. 2015;244(2):637-647."},"year":"2015","type":"journal_article","page":"637-647","_id":"5679","intvolume":" 244","issue":"2","department":[{"_id":"277"}],"title":"Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-probabilistic Uncertainty","language":[{"iso":"eng"}],"date_updated":"2022-01-06T07:02:30Z","oa":"1"}]