Predicting the Performance of Virtual Machine Migration
Sherif Akoush, Ripduman Sohan, Andrew Rice, Andrew W. Moore, Andy Hopper
Abstract
Sherif Akoush, Ripduman Sohan, Andrew Rice, Andrew W. Moore, Andy Hopper
Abstract
With the ability to move virtual machines between physical hosts, live migration is a core feature of virtualisation. However for migration to be useful, deployable feature on a large (datacentre) scale, we need to predict migration times with accuracy. In this paper, we characterise the parameters affecting live migration with particular emphasis on the Xen virtualisation platform. We discuss the relationships between the important parameters that affect migration and highlight how migration performance can vary considerably depending on the workload. We further provide 2 simulation models that are able to predict migration times to within 90% accuracy for both synthetic and real-world benchmarks.
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With the ability to move virtual machines between physical hosts, live migration is a core feature of virtualisation. However for migration to be useful, deployable feature on a large (datacentre) scale, we need to predict migration times with accuracy. In this paper, we characterise the parameters affecting live migration with particular emphasis on the Xen virtualisation platform. We discuss the relationships between the important parameters that affect migration and highlight how migration performance can vary considerably depending on the workload. We further provide 2 simulation models that are able to predict migration times to within 90% accuracy for both synthetic and real-world benchmarks.
Key concepts: Live migration, Virtualization, Virtual machine, Computer science, Workload, Feature (linguistics), Distributed computing, Operating system