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Issue No. 03 - July-Sept. (2015 vol. 3)
ISSN: 2168-7161
pp: 332-344
Bhanu Sharma , Department of Computer Science, University of Manitoba, Winnipeg, Canada
Ruppa K. Thulasiram , Department of Computer Science, University of Manitoba, Winnipeg, Canada
Parimala Thulasiraman , Department of Computer Science, University of Manitoba, Winnipeg, Canada
Rajkumar Buyya , Department of Computing and Information Systems, The University of Melbourne, Parkville, Australia
In Cloud computing, clients would like to pay fair price for the resources while providers would like to make profit for their services. In this study, we propose a Cloud Compute Commodity ($_$C^{3}$_$ ) pricing architecture called Clabacus(Cloud-Abacus) to serve both parties. We use concepts and algorithms from financial option theory to develop Clabacus. We propose a general formula, called compound-Moores law, that captures the technological advances of the resources, rate of inflation and depreciation etc. We map these Cloud parameters to the option pricing parameters to effectively modify the option pricing algorithm in order to compute Cloud resource price. Using financial value-at-risk (VaR) analysis, we adjust the computed resource price to incorporate the inherent risks of the Cloud provider. We propose fuzzy logic and genetic algorithm based approaches to compute the VaR of the provider’s resources. We have incorporated this into our Clabacus architecture. Finally, we study the effects of quality of service, rate of depreciation, rate of inflation, capital investment on the Cloud resource price for both client and provider. We show that if the prices are adjusted within a lower and upper bound, SLA can be guaranteed.
Pricing, Computational modeling, Contracts, Lattices, Cloud computing, Investment, Mathematical model

B. Sharma, R. K. Thulasiram, P. Thulasiraman and R. Buyya, "Clabacus: A Risk-Adjusted Cloud Resources Pricing Model Using Financial Option Theory," in IEEE Transactions on Cloud Computing, vol. 3, no. 3, pp. 332-344, 2015.
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