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Advances, Systems and Applications

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Table 4 Comparison of Multiple VM migration approaches

From: A critical survey of live virtual machine migration techniques

Approach Objective Technique Performance metrics Hypervisor /Simulator
Ye et al. [83]-2011 Focus on different resource reservation method Multiple VM migration with resource reservation & parallel migration strategy and workload-aware migration strategy Downtime, total migration time, and workload performance overheads Xen 3.3.1
Deshpande et al. [84]-2011 Live gang migration De-duplication based approach to perform concurrent live migration of co-located VM’s Reduce the total migration time and network traffic overhead KVM/ QEMU 0.12.3
Lu et al. [85]-2014 Reduce the latency over low network bandwidth and WAN network Investigate the usefulness of two classic algorithms, min-cut and k-means clustering, in determining which VM’s should be co-migrated Imrove both total migration time and network traffic QEMU/ KVM 2.6.32
Lu et al. [86]-2015 Optimal scheduling of multi-tier VM vHaul control multi-VM migrations to figure out the optimal scheduling Minimize service downtime by 70% and improve application throughput by 52% Xen 4.1.2
Forsman et al. [88]-2015 Balance the load Present two strategies (push and pull) to balance the load in a system with multiple VM’s through automated live migration Achieve a load-balanced system in 4-15 minute OMNeT ++ v4.3
Sun et al. [90]-2016 Focus on multiple VM migration problem Proposed serial migration strategy, m mixed migration strategy and develop queuing models Analysis performance metrics like average waiting time, blocking ratio, average waiting queue length, and average queue length of each migration request Xen and KVM