A quantitative study of virtual machine live migration

  • Authors:

  • Wenjin Hu;Andrew Hicks;Long Zhang;Eli M. Dow;Vinay Soni;Hao Jiang;Ronny Bull;Jeanna N. Matthews

  • Affiliations:

  • Clarkson University, Potsdam NY;Clarkson University, Potsdam NY;Clarkson University, Potsdam NY;Clarkson University, Potsdam NY;Clarkson University, Potsdam NY;Clarkson University, Potsdam NY;Clarkson University, Potsdam NY;Clarkson University, Potsdam NY

  • Venue:
  • Proceedings of the 2013 ACM Cloud and Autonomic Computing Conference
  • Year:
  • 2013

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Abstract

Virtual machine (VM) live migration is a critical feature for managing virtualized environments, enabling dynamic load balancing, consolidation for power management, preparation for planned maintenance, and other management features. However, not all virtual machine live migration is created equal. Variants include memory migration, which relies on shared backend storage between the source and destination of the migration, and storage migration, which migrates storage state as well as memory state. We have developed an automated testing framework that measures important performance characteristics of live migration, including total migration time, the time a VM is unresponsive during migration, and the amount of data transferred over the network during migration. We apply this testing framework and present the results of studying live migration, both memory migration and storage migration, in various virtualization systems including KVM, XenServer, VMware, and Hyper-V. The results provide important data to guide the migration decisions of both system administrators and autonomic cloud management systems.