---
_id: '5679'
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.
author:
- first_name: Tim
  full_name: Püschel, Tim
  last_name: Püschel
- first_name: Guido
  full_name: Schryen, Guido
  id: '72850'
  last_name: Schryen
- first_name: Diana
  full_name: Hristova, Diana
  last_name: Hristova
- first_name: Dirk
  full_name: Neumann, Dirk
  last_name: Neumann
citation:
  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.'
  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} }'
  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.'
  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.'
  short: T. Püschel, G. Schryen, D. Hristova, D. Neumann, European Journal of Operational
    Research 244 (2015) 637–647.
date_created: 2018-11-14T15:40:13Z
date_updated: 2022-01-06T07:02:30Z
ddc:
- '000'
department:
- _id: '277'
extern: '1'
file:
- access_level: open_access
  content_type: application/pdf
  creator: hsiemes
  date_created: 2018-12-07T11:44:10Z
  date_updated: 2018-12-13T15:09:12Z
  file_id: '6036'
  file_name: ELSEVIER_JOURNAL_VERSION.pdf
  file_size: 1270024
  relation: main_file
file_date_updated: 2018-12-13T15:09:12Z
has_accepted_license: '1'
intvolume: '       244'
issue: '2'
keyword:
- admission control
- informational uncertainty
- revenue management
- cloud computing
language:
- iso: eng
oa: '1'
page: 637-647
publication: European Journal of Operational Research
publisher: Elsevier
status: public
title: 'Revenue Management for Cloud Computing Providers: Decision Models for Service
  Admission Control under Non-probabilistic Uncertainty'
type: journal_article
user_id: '61579'
volume: 244
year: '2015'
...