Performance modeling of virtual machine live migration

Yangyang Wu, Ming Zhao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

67 Citations (Scopus)

Abstract

System virtualization is becoming pervasive and it is enabling important new computing diagrams such as cloud computing. Live virtual machine (VM) migration is a unique capability of system virtualization which allows applications to be transparently moved across physical machines with a consistent state captured by their VMs. Although live VM migration is generally fast, it is a resource-intensive operation and can impact the application performance and resource usage of the migrating VM as well as other concurrent VMs. However, existing studies on live migration performance are often based on the assumption that there are sufficient resources on the source and destination hosts, which is often not the case for highly consolidated systems. As the scale of virtualized systems such as clouds continue to grow, the use of live migration becomes increasingly more important for managing performance and reliability in such systems. Therefore, it is key to understand the performance of live VM migration under different levels of resource availability. This paper addresses this need by creating performance models for live migration which can be used to predict a VM's migration time given its application's behavior and the resources available to the migration. A series of experiments were conducted on Xen to profile the time for migrating a DomU VM running different resource-intensive applications while DomO is allocated different CPU shares for processing the migration. Regression methods are then used to create the performance model based on the profiling data. The results show that the VM's migration time is indeed substantially impacted by DomO's CPU allocation whereas the performance model can accurately capture this relationship with the coefficient of determination generally higher than 90%.

Original languageEnglish (US)
Title of host publicationProceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011
Pages492-499
Number of pages8
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011 - Washington, DC, United States
Duration: Jul 4 2011Jul 9 2011

Other

Other2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011
CountryUnited States
CityWashington, DC
Period7/4/117/9/11

Fingerprint

Performance Modeling
Virtual Machine
Migration
Computer simulation
Resources
Program processors
Performance Model
Virtualization
Cloud computing
Computer systems
Virtual machine
Availability
Coefficient of Determination
Processing
Profiling
Cloud Computing
Concurrent
Continue
Diagram
Regression

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Applied Mathematics

Cite this

Wu, Y., & Zhao, M. (2011). Performance modeling of virtual machine live migration. In Proceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011 (pp. 492-499). [6008747] https://doi.org/10.1109/CLOUD.2011.109

Performance modeling of virtual machine live migration. / Wu, Yangyang; Zhao, Ming.

Proceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011. 2011. p. 492-499 6008747.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Wu, Y & Zhao, M 2011, Performance modeling of virtual machine live migration. in Proceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011., 6008747, pp. 492-499, 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011, Washington, DC, United States, 7/4/11. https://doi.org/10.1109/CLOUD.2011.109
Wu Y, Zhao M. Performance modeling of virtual machine live migration. In Proceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011. 2011. p. 492-499. 6008747 https://doi.org/10.1109/CLOUD.2011.109
Wu, Yangyang ; Zhao, Ming. / Performance modeling of virtual machine live migration. Proceedings - 2011 IEEE 4th International Conference on Cloud Computing, CLOUD 2011. 2011. pp. 492-499
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