Performance and Revenue Analysis of Hybrid Cloud Federations with QoS Requirements

Hybrid cloud architectures, where private clouds or data centers forward part of their workload to public cloud providers to satisfy quality of service (QoS) requirements, are increasingly common due to the availability of on-demand cloud resources that can be provisioned automatically through programming APIs. In this paper, we analyze performance and revenue in federations of hybrid clouds, where private clouds agree to share part of their local computing resources with other members of the federation. Through resource sharing, underprovisioned members can save on public cloud costs, while overprovisioned members can put their idle resources to work. To reward all hybrid clouds for their contributions (computing resources or workload), public cloud savings due to the federation are distributed among members according to Shapley value. We model this cloud architecture with a continuous-time Markov chain and prove that, if all hybrid clouds have the same QoS requirements, their profits are maximized when they join the federation and share all resources. We also show that this result does not hold when hybrid clouds have different QoS requirements, and we provide a solution to evaluate profit for different resource sharing decisions. Finally, our experimental evaluation compares the distribution of public cloud savings according to Shapley value with alternative approaches, illustrating its ability to discourage free riders of the federation.