Support vector machine approach for virtual machine migration in cloud data center

NCUIR > College of Electrical Engineering & Computer Science > Department of Computer Science and information Engineering > journal & Dissertation > Item 987654321/107328

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Title:	Support vector machine approach for virtual machine migration in cloud data center
Authors:	周立德;Tseng, Fan-Hsun;Chen, Xiaojiao;Chou, Li-Der;Chao, Han-Chieh;Chen, Shiping
Contributors:	資訊電機學院資訊工程學系
Keywords:	Analysis;Cloud computing;Computer centers;Computer Communication Networks;Computer engineering;Computer Science;Data Structures and Information Theory;Energy consumption;Genetic algorithms;Internet;Linear programming;Load;Multimedia computer applications;Multimedia Information Systems;Social networks;Special Purpose and Application-Based Systems;Studies;Support vector machines;User generated content;Workloads
Date:	2015-05-16
Issue Date:	2026-04-23 14:08:10 (UTC+8)
Publisher:	Springer Netherlands;New York: Springer US
Abstract:	摘要： The social media services are popular with Internet services today, such as Facebook, YouTube, Plurk and Twitter. However, the enormous interactions among human beings also result in highly computational costs. The requested resources and demands of some specific social media services are changing severely, and the virtual machines (VMs) exhaust the computing resource of physical machine (PM). Thus this will lead to VM migration. Many researchers investigate how to stabilize the average utilization of virtual machines and physical machines in cloud data center. In this paper, we formulated the VM migration problem in cloud data center based on mixed integer linear programming (MILP). Then, the VM allocation algorithm was proposed to allocate the VMs among the PMs, which is based on the Support Vector Machine (SVM). According to the training process during a specific time, the minimum numbers of VM migration and maximum resource utilization of PMs were accomplished. As the allocation case and simulation results showed, we achieved the stable and low-cost for social media services in cloud data center. 其他題名： Multimed Tools Appl 出版者： New York: Springer US 出版日期： 2015-05-01 出處： Multimedia tools and applications, 2015-05, Vol.74 (10), p.3419-3440 資源來源： ABI/INFORM Collection 版權： Springer Science+Business Media New York 2014 版權： Springer Science+Business Media New York 2015 識別號： ISSN: 1380-7501 識別號： EISSN: 1573-7721 識別號： DOI: 10.1007/s11042-014-2086-z
Appears in Collections:	[Department of Computer Science and information Engineering] journal & Dissertation

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