Making money with clouds: Revenue optimization through automated policy decisions
Many existing IT applications exhibit strongly varying demand patterns for resources.
Accommodating an ever increasing and highly fluctuating demand requires continuous availability of
sufficient resources. To achieve this state at reasonably costs, a high degree of flexibility with respect
to the given IT infrastructure is necessary. Facing this challenge the idea of Cloud computing has
been gaining interest. In so-called Clouds resources such as CPU, storage and bandwidth can be
bundled into a single services, which are offered to Cloud users. These services can be accessed in
oblivion of the underlying IT infrastructure. This way Cloud Computing facilitates the introduction of
new products and services without large investments in the IT infrastructure.
Cloud Computing is a promising approach with a high impact on business models. One aspect of
business models is clearly the revenue model, which defines how prices should be set to achieve
predefined revenue level. The decision about accepting or denying requests has a high impact on the
revenue of the provider. In this paper we analyze two approaches that support the cloud provider in its
decision. We show that predefined policies allow increasing revenue compared to widely used
technical models such as first-come-first-serve.
Pueschel, Tim; Anandasivam, Arun; Buschek, Stefan; and Neumann, Dirk, "Making money with clouds: Revenue optimization through automated policy decisions" (2009). ECIS 2009 Proceedings. 341.