Supporting load-balanced virtual machine placement for cloud infrastructure as a service

Wei Jen Wang, Shao Jui Chen, Jui Hao Yang, Tzu Ming Chan

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

Infrastructure-as-a-service (IaaS) is an important type of cloud service. It integrates conventional computing resources, network resources, storage resources and related software packages into an on-demand network service, which provide virtual resources and machines to the users instead. Therefore, it is important to use a good VM placement mechanism that achieves good performance in an IaaS platform. For example, while allocating resources to a set of virtual machines (VMs), load balance is an important technique to avoid resource usage surge and thus can provide good quality of services to users. In this paper, we present a new VM placement mechanism based on resource usage prediction. The mechanism is implemented on a cloud platform, namely SAMEVED-Stack. The SAMEVED-Stack is a non-commercial cloud platform that supports high-level operations for virtual cluster/datacenter management. It is derived from OpenStack, and designed for supporting on-line network and computer security experiments. Our preliminary results show that, the proposed VM placement strategy outperforms three popular VM placement strategies, the Best-Fit, the First-Fit, and the max-free-memory-fit.

原文???core.languages.en_GB???
主出版物標題Intelligent Systems and Applications - Proceedings of the International Computer Symposium, ICS 2014
編輯William Cheng-Chung Chu, Stephen Jenn-Hwa Yang, Han-Chieh Chao
發行者IOS Press
頁面1396-1405
頁數10
ISBN(電子)9781614994831
DOIs
出版狀態已出版 - 2015
事件International Computer Symposium, ICS 2014 - Taichung, Taiwan
持續時間: 12 12月 201414 12月 2014

出版系列

名字Frontiers in Artificial Intelligence and Applications
274
ISSN(列印)0922-6389

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???event.eventtypes.event.conference???International Computer Symposium, ICS 2014
國家/地區Taiwan
城市Taichung
期間12/12/1414/12/14

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