@article{5679,
  abstract     = {{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       = {{Püschel, Tim and Schryen, Guido and Hristova, Diana and Neumann, Dirk}},
  journal      = {{European Journal of Operational Research}},
  keywords     = {{admission control, informational uncertainty, revenue management, cloud computing}},
  number       = {{2}},
  pages        = {{637--647}},
  publisher    = {{Elsevier}},
  title        = {{{Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-probabilistic Uncertainty}}},
  volume       = {{244}},
  year         = {{2015}},
}