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Although supported by many contemporary Virtual Machine (VM) hypervisors, live migration is impossible for certain applications. When migrating CPU and/or memory intensive VMs two problems occur, extended migration downtime that may cause service interruption or even failure, and prolonged total migration time that is harmful for the overall system performance as significant network resources must be allocated to migration. These problems become more severe for migration over slower networks, such as long distance migration between clouds. We approach this two-fold problem through a combination of techniques. A novel algorithm that dynamically adapts the transfer order of VM memory pages during live migration reduces the risk of re-transfers for frequently dirtied pages. As the amount of transferred data is thereby reduced, the total migration time is shortened. By combining this technique with a compression scheme that increases the migration bandwidth the migration downtime is also reduced. An evaluation by means of synthetic migration benchmarks shows that our combined approach reduces migration downtime by a factor 10 to 20, shortens total migration time by around 35%, as well as consumes between 26% and 39% less network bandwidth. The feasibility of our approach for real-life applications is demonstrated by migrating a streaming video server 31% faster while transferring 51% less data.
Date of Conference: Nov. 29 2011-Dec. 1 2011