• 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