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Title: Traffic-Sensitive Live Migration of Virtual Machines

Conference ·

In this paper we address the problem of network contention between the migration traffic and the VM application traffic for the live migration of co-located Virtual Machines (VMs). When VMs are migrated with pre-copy, they run at the source host during the migration. Therefore the VM applications with predominantly outbound traffic contend with the outgoing migration traffic at the source host. Similarly, during post-copy migration, the VMs run at the destination host. Therefore the VM applications with predominantly inbound traffic contend with the incoming migration traffic at the destination host. Such a contention increases the total migration time of the VMs and degrades the performance of VM application. Here, we propose traffic-sensitive live VM migration technique to reduce the contention of migration traffic with the VM application traffic. It uses a combination of pre-copy and post-copy techniques for the migration of the co-located VMs, instead of relying upon any single pre-determined technique for the migration of all the VMs. We base the selection of migration techniques on VMs' network traffic profiles so that the direction of migration traffic complements the direction of the most VM application traffic. We have implemented a prototype of traffic-sensitive migration on the KVM/QEMU platform. In the evaluation, we compare traffic-sensitive migration against the approaches that use only pre-copy or only post-copy for VM migration. We show that our approach minimizes the network contention for migration, thus reducing the total migration time and the application degradation.

Research Organization:
Argonne National Lab. (ANL), Argonne, IL (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
AC02-06CH11357
OSTI ID:
1335905
Resource Relation:
Conference: 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing, 05/04/15 - 05/07/15, Shenzhen, Guangdong, CN
Country of Publication:
United States
Language:
English

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