research-article

Performance and energy modeling for live migration of virtual machines

Authors:

Cheng-Zhong Xu,

Xiaofei LiaoAuthors Info & Claims

HPDC '11: Proceedings of the 20th international symposium on High performance distributed computing

Pages 171 - 182

https://doi.org/10.1145/1996130.1996154

Published: 08 June 2011 Publication History

Abstract

Live migration of virtual machine (VM) provides a significant benefit for virtual server mobility without disrupting service. It is widely used for system management in virtualized data centers. However, migration costs may vary significantly for different workloads due to the variety of VM configurations and workload characteristics. To take into account the migration overhead in migration decision-making, we investigate design methodologies to quantitatively predict the migration performance and energy cost. We thoroughly analyze the key parameters that affect the migration cost from theory to practice. We construct two application-oblivious models for the cost prediction by using learned knowledge about the workloads at the hypervisor (also called VMM) level. This should be the first kind of work to estimate VM live migration cost in terms of both performance and energy in a quantitative approach. We evaluate the models using five representative workloads on a Xen virtualized environment. Experimental results show that the refined model yields higher than 90% prediction accuracy in comparison with measured cost. Model-guided decisions can significantly reduce the migration cost by more than 72.9% at an energy saving of 73.6%.

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Cited By

Yumoto KYamamoto AMatsuda THiguchi JKodama TUeno HShiraishi T(2025)Virtual Machine Placement Method with Compressed Sensing-Based Traffic Volume EstimationIEICE Transactions on Communications10.23919/transcom.2024EBT0001E108-B:1(72-84)Online publication date: Jan-2025
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Sun JGong ZAgarwal ANoghabi SChandra RSnir MHuang J(2024)Exploring the Efficiency of Renewable Energy-based Modular Data Centers at ScaleProceedings of the 2024 ACM Symposium on Cloud Computing10.1145/3698038.3698544(552-569)Online publication date: 20-Nov-2024
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Mvondo DXing TBarbalace ASchiavoni VEdinger JCao JJin Z(2024)UTwinVM: Reliable hints on the effects of hypervisor updates on VMs in the CloudProceedings of the 25th International Middleware Conference10.1145/3652892.3700752(103-116)Online publication date: 2-Dec-2024
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Index Terms

Performance and energy modeling for live migration of virtual machines
1. Computing methodologies
  1. Modeling and simulation
    1. Model development and analysis
      1. Modeling methodologies
2. Software and its engineering
  1. Software creation and management
    1. Software development process management
      1. Software development methods

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cover image ACM Conferences

HPDC '11: Proceedings of the 20th international symposium on High performance distributed computing

June 2011

296 pages

ISBN:9781450305525

DOI:10.1145/1996130

General Chair:
Arthur "Barney" Maccabe
Oak Ridge National Lab, USA
,
Program Chair:
Douglas Thain
University of Notre Dame, USA

Copyright © 2011 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]

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Published: 08 June 2011

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HPDC '11: The 20th International Symposium on High-Performance Parallel and Distributed Computing

June 8 - 11, 2011

California, San Jose, USA

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https://doi.org/10.23919/transcom.2024EBT0001
Sun JGong ZAgarwal ANoghabi SChandra RSnir MHuang J(2024)Exploring the Efficiency of Renewable Energy-based Modular Data Centers at ScaleProceedings of the 2024 ACM Symposium on Cloud Computing10.1145/3698038.3698544(552-569)Online publication date: 20-Nov-2024
https://dl.acm.org/doi/10.1145/3698038.3698544
Mvondo DXing TBarbalace ASchiavoni VEdinger JCao JJin Z(2024)UTwinVM: Reliable hints on the effects of hypervisor updates on VMs in the CloudProceedings of the 25th International Middleware Conference10.1145/3652892.3700752(103-116)Online publication date: 2-Dec-2024
https://dl.acm.org/doi/10.1145/3652892.3700752
Manterola Lasa ATalluri SDe Matteis TIosup ABalsamo SKnottenbelt WAbad CShang W(2024)The Cost of Simplicity: Understanding Datacenter Scheduler Programming AbstractionsProceedings of the 15th ACM/SPEC International Conference on Performance Engineering10.1145/3629526.3645038(166-177)Online publication date: 7-May-2024
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Afrasiabi SEbrahimzadeh APromwongsa NMouradian CLi WRecse ÁSzabó RGlitho R(2024)Cost-Efficient Cluster Migration of VNFs for Service Function Chain EmbeddingIEEE Transactions on Network and Service Management10.1109/TNSM.2023.328775721:1(979-993)Online publication date: Feb-2024
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Banerjee SRoy SKhatua S(2024)Towards energy and QoS aware dynamic VM consolidation in a multi-resource cloudFuture Generation Computer Systems10.1016/j.future.2024.03.058157(376-391)Online publication date: Aug-2024
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Yuan LWang ZSun PWei Y(2023)An Efficient Virtual Machine Consolidation Algorithm for Cloud ComputingEntropy10.3390/e2502035125:2(351)Online publication date: 14-Feb-2023
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Bartolo ASabry Aly MMichelogiannakis GMitra S(2023)MC-ELMM: Multi-Chip Endurance-Limited Memory ManagementProceedings of the International Symposium on Memory Systems10.1145/3631882.3631905(1-16)Online publication date: 2-Oct-2023
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