标题:An online algorithm for selling your reserved IaaS instances in amazon EC2 marketplace
作者:Yang, Shengsong ;Pan, Li ;Liu, Shijun
通讯作者:Pan, Li
作者机构:[Yang, Shengsong ;Pan, Li ;Liu, Shijun ] School of Software, Shandong University, Jinan; 250101, China
会议名称:26th IEEE International Conference on Web Services, ICWS 2019
会议日期:8 July 2019 through 13 July 2019
来源:Proceedings - 2019 IEEE International Conference on Web Services, ICWS 2019 - Part of the 2019 IEEE World Congress on Services
出版年:2019
页码:296-303
DOI:10.1109/ICWS.2019.00057
关键词:Cloud; Competitive analysis; Cost management; IaaS; Online algorithm
摘要:In cloud platforms such as Amazon EC2, users can reserve IaaS instances rather than buy on-demand ones to save cost. But it would incur the waste of reservations if there are few demands arriving after reserving instances. Currently, there is a reserved instance marketplace launched by Amazon EC2 cloud, where users can sell their unused instances for avoiding such waste of unused reservations. But for users, it is difficult to make the decision to sell their instances optimally without knowing any information for future demands, for it would incur the extra cost when there are new demands arriving after selling their reservations. For solving this problem, an online selling algorithm is proposed in this paper to guide cloud users in selling reserved instances in Amazon EC2 marketplace. We prove theoretically that our online algorithm Aβ can guarantee a bounded competitive ratio of 2T/β, whose value is specific to the type of reserved instances. Taking the i3.large instance provided by Amazon EC2 as an example, the competitive ratio is 3.36 under its pricing rules for 1-year term. Finally, via extensive experiments using workload data collected from actual applications, we verify our online algorithm's effectiveness and demonstrate that it is much more cost effective to cloud users in IaaS platforms. © 2019 IEEE.
收录类别:EI;SCOPUS
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-s2.0-85072767605&doi=10.1109%2fICWS.2019.00057&partnerID=40&md5=2cc58abae92ca239149544656fb601f8
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