DocumentCode :
743780
Title :
Clabacus: A Risk-Adjusted Cloud Resources Pricing Model Using Financial Option Theory
Author :
Sharma, Bhanu ; Thulasiram, Ruppa K. ; Thulasiraman, Parimala ; Buyya, Rajkumar
Author_Institution :
Dept. of Comput. Sci., Univ. of Manitoba, Winnipeg, MB, Canada
Volume :
3
Issue :
3
fYear :
2015
Firstpage :
332
Lastpage :
344
Abstract :
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 (C3) 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.
Keywords :
cloud computing; fuzzy logic; genetic algorithms; pricing; resource allocation; risk management; share prices; C3 pricing architecture; Clabacus architecture; SLA; capital investment; cloud compute commodity pricing architecture; cloud computing; cloud parameters; cloud provider; cloud-abacus; compound-Moores law; depreciation rate; fair price; financial VaR analysis; financial option theory; financial value-at-risk analysis; fuzzy logic; genetic algorithm; inflation rate; option pricing algorithm; option pricing parameters; profit; quality of service; resources technological advances; risk-adjusted cloud resources pricing model; Cloud computing; Computational modeling; Contracts; Investment; Lattices; Mathematical model; Pricing; Clabacus; Resource pricing; financial options; fuzzy logic; genetic algorithm; value-at-risk;
fLanguage :
English
Journal_Title :
Cloud Computing, IEEE Transactions on
Publisher :
ieee
ISSN :
2168-7161
Type :
jour
DOI :
10.1109/TCC.2014.2382099
Filename :
6987297
Link To Document :
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