TY - GEN
T1 - Experimental study of virtual machine migration in support of reservation of cluster resources
AU - Zhao, Ming
AU - Figueiredo, Renato J.
N1 - Funding Information:
★ Partially supported by the CNR activities DG.RSTL.050.008, ICT.P10.009.001 and the Austrian Science Fund (FWF) grant no. P20134-N13.
PY - 2007
Y1 - 2007
N2 - Virtual Machines are becoming increasingly valuable to resource consolidation and management, providing efficient and secure resource containers, along with desired application execution environments. This paper focuses on the VM-based resource reservation problem, that is, the reservations of CPU, memory and network resources for individual VM instances, as well as for VM clusters. In particular, it considers the scenario where one or several physical servers need to be vacated to start a cluster of VMs for dedicated execution of parallel jobs. VMs provide a primitive for transparently vacating workloads through migration; however, the process of migrating several VMs can be time-consuming and needs to be estimated. To achieve this goal, this paper seeks to provide a model that can characterize the VM migration process and predict its performance, based on a comprehensive experimental analysis. The results show that, given a certain VM's migration time, it is feasible to predict the time for a VM with other configurations, as well as the time for migrating a number of VMs. The paper also shows that migration of VMs in parallel results in shorter aggregate migration times, but with higher per-VM migration latencies. Experimental results also quantify the benefits of buffering the state of migrated VMs in main memory without committing to hard disks.
AB - Virtual Machines are becoming increasingly valuable to resource consolidation and management, providing efficient and secure resource containers, along with desired application execution environments. This paper focuses on the VM-based resource reservation problem, that is, the reservations of CPU, memory and network resources for individual VM instances, as well as for VM clusters. In particular, it considers the scenario where one or several physical servers need to be vacated to start a cluster of VMs for dedicated execution of parallel jobs. VMs provide a primitive for transparently vacating workloads through migration; however, the process of migrating several VMs can be time-consuming and needs to be estimated. To achieve this goal, this paper seeks to provide a model that can characterize the VM migration process and predict its performance, based on a comprehensive experimental analysis. The results show that, given a certain VM's migration time, it is feasible to predict the time for a VM with other configurations, as well as the time for migrating a number of VMs. The paper also shows that migration of VMs in parallel results in shorter aggregate migration times, but with higher per-VM migration latencies. Experimental results also quantify the benefits of buffering the state of migrated VMs in main memory without committing to hard disks.
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U2 - 10.1145/1408654.1408659
DO - 10.1145/1408654.1408659
M3 - Conference contribution
AN - SCOPUS:84869259086
SN - 9781595938978
T3 - VTDC'07: Proceedings of the 3rd International Workshop on Virtualization Technology in Distributed Computing
BT - VTDC'07
T2 - 3rd International Workshop on Virtualization Technology in Distributed Computing 2007, VTDC'07
Y2 - 12 November 2007 through 12 November 2007
ER -