Comparison of Two Yield Management Strategies for Cloud Service Providers
AbstractSeveral 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.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoPaper provided by Seoul National University; Technology Management, Economics, and Policy Program (TEMEP) in its series TEMEP Discussion Papers with number 2013103.
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).
Cloud Computing; Revenue Management; Pricing Strategy; Autonomic Resource Management.;
Find related papers by JEL classification:
- C61 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Optimization Techniques; Programming Models; Dynamic Analysis
- C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
- D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
- L86 - Industrial Organization - - Industry Studies: Services - - - Information and Internet Services; Computer Software
- M15 - Business Administration and Business Economics; Marketing; Accounting - - Business Administration - - - IT Management
This paper has been announced in the following NEP Reports:
- NEP-ALL-2013-05-19 (All new papers)
- NEP-CMP-2013-05-19 (Computational Economics)
- NEP-CWA-2013-05-19 (Central & Western Asia)
You can help add them by filling out this form.
reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Jorn Altmann).
If references are entirely missing, you can add them using this form.