An Optimal and Iterative Pricing Model for Multiclass IaaS Cloud Services

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• 关键词：Pricing ; IaaS ; Cloud computing ; Profit maximization
• 刊名：Lecture Notes in Computer Science
• 出版年：2016
• 出版时间：2016
• 年：2016
• 卷：9936
• 期：1
• 页码：597-605
• 全文大小：325 KB
• 参考文献：1.Armbrust, M., Fox, A., Griffith, R., Joseph, A.D., Katz, R., Konwinski, A., Lee, G., Patterson, D., Rabkin, A., Stoica, I., Zaharia, M.: A view of cloud computing. Commun. ACM 53, 50–58 (2010)CrossRef
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• 作者单位：Shuo Zhang (17)
  Li Pan (17)
  Shijun Liu (17)
  Lei Wu (17)
  Lizhen Cui (17)
  Dong Yuan (18)
  
  17. School of Computer Science and Technology, Shandong University, Jinan, 250101, China
  18. School of Electrical and Information Engineering, The University of Sydney, Sydney, Australia
  
• 丛书名：Service-Oriented Computing
• ISBN：978-3-319-46295-0
• 刊物类别：Computer Science
• 刊物主题：Artificial Intelligence and Robotics
  Computer Communication Networks
  Software Engineering
  Data Encryption
  Database Management
  Computation by Abstract Devices
  Algorithm Analysis and Problem Complexity
  
• 出版者：Springer Berlin / Heidelberg
• ISSN：1611-3349
• 卷排序：9936

文摘

In this paper, we investigate optimal pricing models for profit maximization from the perspective of cloud providers in the presence of multiple classes of IaaS (Infrastructure as a Service) services. We propose an iterative model in which a cloud provider iteratively posts updated prices for the multiple classes of IaaS instances to users until reaching convergence that maximizes its profit. During this process, any interested user can determine the optimal class of IaaS instances and the optimal quantity to buy according to its own private utility function. In particular, we propose two algorithms to implement the iterative pricing process: a Genetic based near-optimal algorithm, and a hill climbing based cost-effective algorithm. The experimental results show that our iterative pricing algorithms can achieve advanced profitability in pricing multiclass IaaS instances in cloud environments.