skip to main content
10.1145/2806777.2806838acmconferencesArticle/Chapter ViewAbstractPublication PagesmodConference Proceedingsconference-collections
research-article

Towards a comprehensive performance model of virtual machine live migration

Published:27 August 2015Publication History

ABSTRACT

Although many models exist to predict the time taken to migrate a virtual machine from one physical machine to another, our empirical validation of these models has shown the 90th percentile error to be 46% (43 secs) and 159% (112 secs) for KVM and Xen live migration, respectively. Our analysis reveals that these models are fundamentally flawed as they all fail to take into account the following three critical parameters: (i) the writable working set size, (ii) the number of pages eligible for the skip technique, (iii) the relation of the number of skipped pages with the page dirty rate and the page transfer rate, and incorrectly model the key parameter---the number of new pages dirtied per unit time. In this paper, we propose a novel model that takes all these parameters into account. We present a thorough validation with 53 workloads and show that the 90th percentile error in the estimated migration times is only 12% (8 secs) and 19% (14 secs) for KVM and Xen live migration, respectively.

References

  1. Dell DVD Store: http://linux.dell.com/dvdstore/.Google ScholarGoogle Scholar
  2. S. Akoush, R. Sohan, A. Rice, A. Moore, and A. Hopper. Predicting the Performance of Virtual Machine Migration. In IEEE MASCOTS, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. A. Aldhalaan and D. Menasc. Analytic Performance Modeling and Optimization of Live VM Migration. Computer Performance Engineering, LNCS, 2013.Google ScholarGoogle Scholar
  4. C. Bienia, S. Kumar, J. P. Singh, and K. Li. The PARSEC Benchmark Suite: Characterization and Architectural Implications. In PACT, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. N. Bila, E. de Lara, K. Joshi, H. A. Lagar-Cavilla, M. Hiltunen, and M. Satyanarayanan. Jettison: Efficient Idle Desktop Consolidation with Partial VM Migration. In EuroSys, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. S. M. Blackburn, R. Garner, and C. Hoffmann. The DaCapo Benchmarks: Java Benchmarking Development and Analysis. In OOPSLA, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. D. Breitgand, G. Kutiel, and D. Raz. Cost-aware live migration of services in the cloud. In Hot-ICE, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. H. W. Choi, H. Kwak, A. Sohn, and K. Chung. Autonomous Learning for Efficient Resource Utilization of Dynamic VM Migration. In ICS, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. C. Clark, K. Fraser, S. Hand, J. G. Hansen, E. Jul, C. Limpach, I. Pratt, and A. Warfield. Live Migration of Virtual Machines. In NSDI, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. T. Das, P. Padala, V. N. Padmanabhan, R. Ramjee, and K. G. Shin. LiteGreen: Saving Energy in Networked Desktops Using Virtualization. In USENIX ATC, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. L. Deng, H. Jin, H. Chen, and S. Wu. Migration Cost Aware Mitigating Hot Nodes in the Cloud. In CloudCom-Asia, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. D. E. Difallah, A. Pavlo, C. Curino, and P. Cudr-Mauroux. OLTP-Bench: An Extensible Testbed for Benchmarking Relational Databases. In PVLDB, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. J. J. Dongarra, P. Luszczek, and A. Petitet. The LINPACK benchmark: Past, present, and future. In Concurrency and Computation: Practice and Experience, 2003.Google ScholarGoogle ScholarCross RefCross Ref
  14. T. Guo, U. Sharma, P. Shenoy, T. Wood, and S. Sahu. Cost-Aware Cloud Bursting for Enterprise Applications. In ACM Transaction on Internet Technology, 2014. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. E. Halili. Apache JMeter. Packt Publishing, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. J. Heo, X. Zhu, P. Padala, and Z. Wang. Memory overbooking and dynamic control of Xen virtual machines in consolidated environments. In IFIP/IEEE IM, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. J. Jeong, S.-H. Kim, H. Kim, J. Lee, and E. Seo. Analysis of Virtual Machine Live-migration As a Method for Power-capping. In Journal of Supercomputing, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. A. Kivity. kvm: The Linux Virtual Machine Monitor. In OLS, 2007.Google ScholarGoogle Scholar
  19. S. Kumar, V. Talwar, V. Kumar, P. Ranganathan, and K. Schwan. vManage: Loosely Coupled Platform and Virtualization Management in Data Centers. In ICAC, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  20. S. Kurtz, A. Phillippy, A. Delcher, M. Smoot, M. Shumway, C. Antonescu, and S. Salzberg. Versatile and open software for comparing large genomes. In Genome Biology, 2004.Google ScholarGoogle Scholar
  21. J. Li, J. Zhao, Y. Li, L. Cui, B. Li, L. Liu, and J. Panneerselvam. iMIG: Toward an Adaptive Live Migration Method for KVM Virtual Machines. In The Computer Journal, 2014.Google ScholarGoogle Scholar
  22. H. Liu and B. He. VMbuddies: Coordinating Live Migration of Multi-Tier Applications in Cloud Environments. In IEEE Transactions on Parallel and Distributed Systems, 2014.Google ScholarGoogle Scholar
  23. H. Liu, C.-Z. Xu, H. Jin, J. Gong, and X. Liao. Performance and Energy Modeling for Live Migration of Virtual Machines. In HPDC, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  24. V. Mann, A. Gupta, P. Dutta, A. Vishnoi, P. Bhattacharya, R. Poddar, and A. Iyer. Remedy: Network-Aware Steady State VM Management for Data Centers. In NETWORKING, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. MediaWiki. MediaWiki, 2011.Google ScholarGoogle Scholar
  26. M. Mishra, A. Das, P. Kulkarni, and A. Sahoo. Dynamic resource management using virtual machine migrations. In IEEE Communications Magazine, 2012.Google ScholarGoogle ScholarCross RefCross Ref
  27. R. Narayanan, B. Ozisikyilmaz, J. Zambreno, G. Memik, and A. Choudhary. MineBench: A Benchmark Suite for Data Mining Workloads. In IISWC, 2006.Google ScholarGoogle ScholarCross RefCross Ref
  28. S. Nathan, P. Kulkarni, and U. Bellur. Resource Availability Based Performance Benchmarking of Virtual Machine Migrations. In ICPE, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  29. M. Nelson, B.-H. Lim, and G. Hutchins. Fast Transparent Migration for Virtual Machines. In USENIX ATC, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. H. Nguyen, Z. Shen, X. Gu, S. Subbiah, and J. Wilkes. AGILE: Elastic Distributed Resource Scaling for Infrastructure-as-a-Service. In ICAC, 2013.Google ScholarGoogle Scholar
  31. P. Padala, K.-Y. Hou, K. G. Shin, X. Zhu, M. Uysal, Z. Wang, S. Singhal, and A. Merchant. Automated Control of Multiple Virtualized Resources. In EuroSys, 2009. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. T.-I. Salomie, G. Alonso, T. Roscoe, and K. Elphinstone. Application Level Ballooning for Efficient Server Consolidation. In EuroSys, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  33. U. B. Senthil Nathan and P. Kulkarni. An Empirical Evaluation of Optimization Techniques for Virtual Machine Migration, 2015.Google ScholarGoogle Scholar
  34. V. Shrivastava, P. Zerfos, K.-W. Lee, H. Jamjoom, Y.-H. Liu, and S. Banerjee. Application-aware virtual machine migration in data centers. In IEEE INFOCOM, 2011.Google ScholarGoogle ScholarCross RefCross Ref
  35. R. Singh, D. Irwin, P. Shenoy, and K. K. Ramakrishnan. Yank: Enabling Green Data Centers to Pull the Plug. In NSDI, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. J. Sonnek, J. Greensky, R. Reutiman, and A. Chandra. Starling: Minimizing Communication Overhead in Virtualized Computing Platforms Using Decentralized Affinity-Aware Migration. In ICPP, 2010. Google ScholarGoogle ScholarDigital LibraryDigital Library
  37. J. Spacco and W. Pugh. RUBiS Revisited: Why J2EE Benchmarking is Hard. 2005.Google ScholarGoogle Scholar
  38. S. Sudevalayam and P. Kulkarni. Affinity-aware Modeling of CPU Usage with Communicating Virtual Machines. In Journal of Systems and Software, 2013.Google ScholarGoogle Scholar
  39. P. Svärd, B. Hudzia, J. Tordsson, and E. Elmroth. Evaluation of Delta Compression Techniques for Efficient Live Migration of Large Virtual Machines. In VEE, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  40. D. Williams, H. Jamjoom, Y.-H. Liu, and H. Weatherspoon. Overdriver: Handling Memory Overload in an Oversubscribed Cloud. In VEE, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  41. D. Williams, H. Jamjoom, and H. Weatherspoon. The Xen-Blanket: Virtualize Once, Run Everywhere. In EuroSys, 2012. Google ScholarGoogle ScholarDigital LibraryDigital Library
  42. T. Wood, P. Shenoy, A. Venkataramani, and M. Yousif. Black-box and Gray-box Strategies for Virtual Machine Migration. In NSDI, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  43. Y. Wu and M. Zhao. Performance Modeling of Virtual Machine Live Migration. In IEEE CLOUD, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. F. Xu, F. Liu, L. Liu, H. Jin, B. Li, and B. Li. iAware: Making Live Migration of Virtual Machines Interference-Aware in the Cloud. In IEEE Transactions on Computers, 2013. Google ScholarGoogle ScholarDigital LibraryDigital Library
  45. J. Xu, M. Zhao, J. Fortes, R. Carpenter, and M. Yousif. Autonomic Resource Management in Virtualized Data Centers Using Fuzzy Logic-based Approaches. In Cluster Computing, 2008. Google ScholarGoogle ScholarDigital LibraryDigital Library
  46. J. Zhang, F. Ren, and C. Lin. Delay Guaranteed Live Migration of Virtual Machines. IEEE INFOCOM, 2014.Google ScholarGoogle ScholarCross RefCross Ref
  47. J. Zheng, T. Ng, K. Sripanidkulchai, and Z. Liu. Pacer: A Progress Management System for Live Virtual Machine Migration in Cloud Computing. In IEEE Transactions on Network and Service Management, 2013.Google ScholarGoogle Scholar
  48. J. Zheng, T. S. E. Ng, and K. Sripanidkulchai. Workload-aware Live Storage Migration for Clouds. In VEE, 2011. Google ScholarGoogle ScholarDigital LibraryDigital Library
  1. Towards a comprehensive performance model of virtual machine live migration

      Recommendations

      Comments

      Login options

      Check if you have access through your login credentials or your institution to get full access on this article.

      Sign in
      • Published in

        cover image ACM Conferences
        SoCC '15: Proceedings of the Sixth ACM Symposium on Cloud Computing
        August 2015
        446 pages
        ISBN:9781450336512
        DOI:10.1145/2806777

        Copyright © 2015 ACM

        Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

        Publisher

        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 27 August 2015

        Permissions

        Request permissions about this article.

        Request Permissions

        Check for updates

        Qualifiers

        • research-article

        Acceptance Rates

        SoCC '15 Paper Acceptance Rate34of157submissions,22%Overall Acceptance Rate169of722submissions,23%

      PDF Format

      View or Download as a PDF file.

      PDF

      eReader

      View online with eReader.

      eReader