Volume 244, Issue 2, 16 July 2015, Pages 637–647
Revenue Management for Cloud Computing Providers
Decision Models for Service Admission Control under
Non-probabilistic Uncertainty
Tim P¨uschela, Guido Schryenb,, Diana Hristovab, Dirk Neumanna
aChair for Information Systems Research, Albert-Ludwigs-Universit¨at Freiburg, Platz der
Alten Synagoge, 79108 Freiburg, Germany
bManagement Information Systems, Universit¨at Regensburg, Universit¨atsstr. 31, 93053
Regensburg, Germany
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. Allowing
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 models
that aim at maximizing the revenue of Cloud providers while taking informational
uncertainty regarding resource requirements into account. Our
evaluation shows that policy-based approaches statistically significantly outperform
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.
Keywords: admission control, informational uncertainty, revenue
management, cloud computing
دانلود مقاله Revenue Management for Cloud Computing Providers: Decision Models for Service Admission Control under Non-probabilistic Uncertainty - انتشار 2015