RO-BURST: A Robust Virtualization Cost Model for Workload Consolidation over Clouds
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Selling T-shirts and Time Shares in the Cloud
CCGRID '12 Proceedings of the 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012)
Modeling and performance analysis of large scale IaaS Clouds
Future Generation Computer Systems
Cost models - pillars for efficient cloud computing: position paper
International Journal of Intelligent Systems Technologies and Applications
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Virtualization offers the potential for cost-effective service provisioning. For service providers who make significant investments in new virtualized data centers in support of private or public clouds, one of the serious challenges is the problem of recovering costs for new server hardware, software, network, storage, management, etc. Gaining visibility and accurately determining the cost of shared resources used by collocated services is essential for implementing a proper chargeback approach in cloud environments. We introduce and compare three different models for apportioning cost and champion the one that is least sensitive to workload placement decisions and provides the most robust and repeatable cost estimates. A detailed study involving 312 workloads from an HP customer environment demonstrates the result. Finally, we employ the cost model in a case study that evaluates the impact on the cost of exploiting different virtualization platform alternatives for the 312 workloads. For example, some workloads may cost more to host using certain virtualization platforms than on others or on standalone hosts. We demonstrate different decision points with potential cost savings of nearly 20% by "right-virtualizing" the workloads.