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Comparison of Two Yield Management Strategies for Cloud Service Providers


Author Info

  • Mohammad Mahdi Kashef

    (TEMEP, College of Engineering, Seoul National University)

  • Azamat Uzbekov

    (TEMEP, College of Engineering, Seoul National University)

  • Jorn Altmann

    (TEMEP, College of Engineering, Seoul National University)

  • Matthias Hovestadt

    (Department of Computer Science, Hanover University of Applied Sciences)


Several Cloud computing business models have been developed and implemented, including dynamic pricing schemes. This paper extends the known concepts of revenue management to the specific case of Cloud computing from two perspectives. First, we propose system architecture for Cloud service providers for combining demand-based pricing and scheduling. Second, a comparison of two yield management methods for cloud computing has been compared: Limited Discount Period Algorithm and VM Reservation Level Algorithm. By taking advantage of demand estimation, the two algorithms find the optimum number of VMs that are sold at full price and the optimum time period before the allocation when the prices should change. Simulation results show that both yield management methods outperform static pricing models and the algorithms perform differently considering the deviation of demand.

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Bibliographic Info

Paper provided by Seoul National University; Technology Management, Economics, and Policy Program (TEMEP) in its series TEMEP Discussion Papers with number 2013103.

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Length: 17 pages
Date of creation: May 2013
Date of revision: May 2013
Publication status: Published in Proceedings of the 8th International Conference on Grid and Pervasive Computing (GPC 2013).
Handle: RePEc:snv:dp2009:2013103

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Related research

Keywords: Cloud Computing; Revenue Management; Pricing Strategy; Autonomic Resource Management.;

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