Cluster Computing and the Grid, IEEE International Symposium on (2012)
May 13, 2012 to May 16, 2012
In this study, we design, develop, and simulate a cloud resources pricing model that satisfies two important constraints: the dynamic ability of the model to provide a high satisfaction guarantee measured as Quality of Service (QoS) - from users perspectives, profitability constraints - from the cloud service providers perspectives We employ financial option theory and treat the cloud resources as underlying assets to capture the realistic value of the cloud compute commodities (C3). We then price the cloud resources using our model. We discuss the results for four different metrics that we introduce to guarantee the quality of service and price as follows: (a) Moore's law based depreciation of asset values, (b) new technology based volatility measures in capturing price changes, (c) a new financial option pricing based model combining the above two concepts, and (d) the effect of age of resources and depreciation of cloud resource on QoS. We show that the cloud parameters can be mapped to financial economic model and we discuss the results of cloud compute commodity pricing for various parameters, such as the age of the resource, quality of service, and contract period.
Cloud Resources Pricing, Financial Economic Model, Depreciation of Resources, Quality of Service, Profit
R. K. Thulasiram, P. Thulasiraman, S. K. Garg, B. Sharma and R. Buyya, "Pricing Cloud Compute Commodities: A Novel Financial Economic Model," Cluster Computing and the Grid, IEEE International Symposium on(CCGRID), Ottawa, Canada, 2012, pp. 451-457.