Support vector machine approach for virtual machine migration in cloud data center
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  • 作者:Fan-Hsun Tseng ; Xiaojiao Chen ; Li-Der Chou&#8230
  • 关键词:Social media service ; Load balance ; Support vector machine ; Mixed integer linear programming ; Cloud data center
  • 刊名:Multimedia Tools and Applications
  • 出版年:2015
  • 出版时间:May 2015
  • 年:2015
  • 卷:74
  • 期:10
  • 页码:3419-3440
  • 全文大小:3,810 KB
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  • 作者单位:Fan-Hsun Tseng (1)
    Xiaojiao Chen (2)
    Li-Der Chou (1)
    Han-Chieh Chao (3) (4)
    Shiping Chen (5)

    1. Department of Computer Science and Information Engineering, National Central University, No. 300, Jhongda Rd., Jhongli, Taoyuan County, Taiwan, 32001, Republic of China
    2. School of Optical-Electrical and Computer Engineering, University of Shanghai for Science and Technology, No. 516, Jun Gong Road, Shanghai, 200093, Peoples鈥檚 Republic of China
    3. Department of Electronic Engineering & Department of Computer Science and Information Engineering, National I-Lan University, No. 1, Sec. 1, Shen-Lung Road, I-Lan, Taiwan, 26047, Republic of China
    4. Department of Electrical Engineering, National Dong Hwa University, No. 1, Sec. 2, Da Hsueh Rd., Shoufeng, Hualien, 97401, Taiwan
    5. School of Optical-Electrical and Computer Engineering & Network Center, University of Shanghai for Science and Technology, No. 516, Jun Gong Road, Shanghai, 200093, Peoples鈥檚 Republic of China
  • 刊物类别:Computer Science
  • 刊物主题:Multimedia Information Systems
    Computer Communication Networks
    Data Structures, Cryptology and Information Theory
    Special Purpose and Application-Based Systems
  • 出版者:Springer Netherlands
  • ISSN:1573-7721
文摘
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.

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