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MigVisor: Accurate Prediction of VM Live Migration Behavior using a Working-Set Pattern Model

Published: 08 April 2017 Publication History

Abstract

Live migration of a virtual machine (VM) is a powerful technique with benefits of server maintenance, resource management, dynamic workload re-balance, etc. Modern research has effectively reduced the VM live migration (VMLM) time to dozens of milliseconds, but live migration still exhibits failures if it cannot terminate within the given time constraint. The ability to predict this type of failure can avoid wasting networking and computing resources on the VM migration, and the associated system performance degradation caused by wasting these resources. The cost of VM live migration highly depends on the application workload of the VM, which may undergo frequent changes. At the same time, the available system resources for VM migration can also change substantially and frequently. To account for these issues, we present a solution called MigVisor, which can accurately predict the behaviour of VM migration using working-set model. This can enable system managers to predict the migration cost and enhance the system management efficacy. The experimental results prove the design suitability and show that the MigVisor has a high prediction accuracy since the average relative error between the predicted value and the measured value is only 6.2%~9%.

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cover image ACM Conferences
VEE '17: Proceedings of the 13th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments
April 2017
261 pages
ISBN:9781450349482
DOI:10.1145/3050748
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 April 2017

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Author Tags

  1. live migration
  2. prediction
  3. virtual machine

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VEE '17

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VEE '17 Paper Acceptance Rate 18 of 43 submissions, 42%;
Overall Acceptance Rate 80 of 235 submissions, 34%

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Cited By

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  • (2022)Memory/Disk Operation Aware Lightweight VM Live MigrationIEEE/ACM Transactions on Networking10.1109/TNET.2022.315593530:4(1895-1910)Online publication date: Aug-2022
  • (2019)Memory/Disk Operation Aware Lightweight VM Live Migration Across Data-centers with Low Performance ImpactIEEE INFOCOM 2019 - IEEE Conference on Computer Communications10.1109/INFOCOM.2019.8737639(334-342)Online publication date: Apr-2019
  • (2019)Interference and Topology-Aware VM Live Migrations in Software-Defined Networks2019 IEEE 21st International Conference on High Performance Computing and Communications; IEEE 17th International Conference on Smart City; IEEE 5th International Conference on Data Science and Systems (HPCC/SmartCity/DSS)10.1109/HPCC/SmartCity/DSS.2019.00152(1068-1075)Online publication date: Aug-2019
  • (2019)An Experience-Based Scheme for Energy-SLA Balance in Cloud Data CentersIEEE Access10.1109/ACCESS.2019.28991017(23500-23513)Online publication date: 2019
  • (2019)Efficient live virtual machine migration for memory write-intensive workloadsFuture Generation Computer Systems10.1016/j.future.2018.12.048Online publication date: Jan-2019
  • (2024)Optimizing pre-copy live virtual machine migration in cloud computing using machine learning-based prediction modelComputing10.1007/s00607-024-01318-6106:9(3031-3062)Online publication date: 8-Jul-2024
  • (2023)A Novel Sustainable Bandwidth Allocation Strategy for Multiple Service Migration in 5G/6G Edge ComputingGLOBECOM 2023 - 2023 IEEE Global Communications Conference10.1109/GLOBECOM54140.2023.10437401(1-7)Online publication date: 4-Dec-2023
  • (2022)Memory/Disk Operation Aware Lightweight VM Live MigrationIEEE/ACM Transactions on Networking10.1109/TNET.2022.315593530:4(1895-1910)Online publication date: Aug-2022
  • (2021)Extending Intel PML for hardware-assisted working set size estimation of VMsProceedings of the 17th ACM SIGPLAN/SIGOPS International Conference on Virtual Execution Environments10.1145/3453933.3454018(111-124)Online publication date: 7-Apr-2021
  • (2019)Online Live VM Migration Algorithms to Minimize Total Migration Time and Downtime2019 IEEE International Parallel and Distributed Processing Symposium (IPDPS)10.1109/IPDPS.2019.00051(406-417)Online publication date: May-2019
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