标题:An Optimal and Iterative Pricing Model for Multiclass IaaS Cloud Services
作者:Zhang, Shuo; Pan, Li; Liu, Shijun; Wu, Lei; Cui, Lizhen; Yuan, Dong
通讯作者:Pan, Li
作者机构:[Zhang, Shuo; Pan, Li; Liu, Shijun; Wu, Lei; Cui, Lizhen] Shandong Univ, Sch Comp Sci & Technol, Jinan 250101, Peoples R China.; [Yuan, Dong] Univ S 更多
会议名称:14th International Conference on Service-Oriented Computing (ICSOC)
会议日期:OCT 10-13, 2016
来源:SERVICE-ORIENTED COMPUTING, (ICSOC 2016)
出版年:2016
卷:9936
页码:597-605
DOI:10.1007/978-3-319-46295-0_39
关键词:Pricing; IaaS; Cloud computing; Profit maximization
摘要: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.
收录类别:CPCI-S;EI;SCOPUS
WOS核心被引频次:2
Scopus被引频次:3
资源类型:会议论文;期刊论文
原文链接:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84989332840&doi=10.1007%2f978-3-319-46295-0_39&partnerID=40&md5=f24228da38db912e5ba4a8a23f55bf5a
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