• DocumentCode
    3739531
  • Title

    WAIO: Improving Virtual Machine Live Storage Migration for the Cloud by Workload-Aware IO Outsourcing

  • Author

    Yaodong Yang;Hong Jiang;Bo Mao;Lei Tian;Yuekun Yang;Junjie Qian

  • Author_Institution
    Dept. of Comput. Sci. &
  • fYear
    2015
  • Firstpage
    314
  • Lastpage
    321
  • Abstract
    Virtual Machine (VM) live storage migration is widely performed in the current cloud data centers, for the purposes of load balance, hardware maintenance and system upgrade. Nevertheless, conventional migration approaches, such as Dirty Block Tracking (DBT), do not address the problem of IO interference between VM IO requests and Migration IO requests during the migration period, which degrades both the VM IO performance and the migration performance. In this paper, we propose a Workload-Aware IO Outsourcing scheme, short for WAIO, to improve the VM live storage migration efficiency. WAIO effectively outsources the VM´s working set to a surrogate device during the migration and creates separate IO path for servicing the VM IO requests. By outsourcing VM IO requests from the original storage to the surrogate device, the VM live storage migration process can be performed on the original storage, no longer interfered, while the outsourced VM IO requests are serviced separately and thus much more quickly. Our lightweight prototype implementation of WAIO and extensive trace-driven experiments demonstrate that, compared with the existing migration approach DBT, WAIO significantly improves the VM´s IO performance during the migration process. Moreover, WAIO allows the hypervisor to migrate a VM at a higher migration speed, without sacrificing the VM´s IO performance.
  • Keywords
    "Cloud computing","Performance evaluation","Interference","Servers","Virtual machine monitors","Outsourcing","Electronic mail"
  • Publisher
    ieee
  • Conference_Titel
    Cloud Computing Technology and Science (CloudCom), 2015 IEEE 7th International Conference on
  • Type

    conf

  • DOI
    10.1109/CloudCom.2015.34
  • Filename
    7396172