Physical resources are highly virtualized in todays datacenter-based cloud-computing networks. Servers, for example, are virtualized as Virtual Machines (VMs). Through abstraction of physical resources, server virtualization enables migration of VMs over the interconnecting network. VM migration can be used for load balancing, energy conservation, disaster protection, etc. Migration of a VM involves iterative memory copy and network re-configuration. Memory states are transferred in multiple phases to keep the VM alive during the migration process, with a small downtime for switchover. Significant network resources are consumed during this process. Migration also results in undesirable performance impacts. Suboptimal network bandwidth assignment, inaccurate pre-copy iterations, and high end-to-end network delay in wide-area networks (WAN) can exacerbate the performance degradation. In this study, we devise strategies to find suitable bandwidth and pre-copy iteration count to optimize different performance metrics of VM migration over a WAN. First, we formulate models to measure network resource consumption, migration duration, and migration downtime. Then, we propose a strategy to determine appropriate migration bandwidth and number of pre-copy iterations, and perform numerical experiments in multiple cloud environments with large number of migration requests. Results show that our approach consumes less network resources when compared with maximum and minimum-bandwidth provisioning strategies while using an order of magnitude less bandwidth than maximum-bandwidth strategy. It also achieves significantly lower migration duration than minimum-bandwidth scheme.

Bandwidth provisioning for virtual machine migration in cloud: Strategy and application

Tornatore, Massimo;
2018-01-01

Abstract

Physical resources are highly virtualized in todays datacenter-based cloud-computing networks. Servers, for example, are virtualized as Virtual Machines (VMs). Through abstraction of physical resources, server virtualization enables migration of VMs over the interconnecting network. VM migration can be used for load balancing, energy conservation, disaster protection, etc. Migration of a VM involves iterative memory copy and network re-configuration. Memory states are transferred in multiple phases to keep the VM alive during the migration process, with a small downtime for switchover. Significant network resources are consumed during this process. Migration also results in undesirable performance impacts. Suboptimal network bandwidth assignment, inaccurate pre-copy iterations, and high end-to-end network delay in wide-area networks (WAN) can exacerbate the performance degradation. In this study, we devise strategies to find suitable bandwidth and pre-copy iteration count to optimize different performance metrics of VM migration over a WAN. First, we formulate models to measure network resource consumption, migration duration, and migration downtime. Then, we propose a strategy to determine appropriate migration bandwidth and number of pre-copy iterations, and perform numerical experiments in multiple cloud environments with large number of migration requests. Results show that our approach consumes less network resources when compared with maximum and minimum-bandwidth provisioning strategies while using an order of magnitude less bandwidth than maximum-bandwidth strategy. It also achieves significantly lower migration duration than minimum-bandwidth scheme.
2018
Bandwidth optimization; Bandwidth provisioning; Cloud networks; Live vm migration; Virtual network function (vnf); Vm memory dirtying rate; Software; Information Systems; Hardware and Architecture; Computer Science Applications1707 Computer Vision and Pattern Recognition; Computer Networks and Communications
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11311/1079345
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