Nowadays, cloud computing is rigorously used by academicians as well as by researchers due to its excellent applicability. Most significant feature of cloud computing is Live Migration of Virtual Machines (VMs). However, it demands large amount of migration time to transfer data from source to destination. Migration time of VMs can be mitigated by several techniques available in study. In migration, scheduling also plays a vital role which handles the processes, task, resources, etc. FCFS (first come, first serve), RR (round robin), and SJF (shortest job first) are among the several scheduling algorithms in CPU scheduling, utilized for minimization of makespan. In this paper, a more optimized scheduling algorithm known as MLFQ (multilevel feedback queue) is utilized. MLFQ helps in minimizing the makespan and overall workload with the help of feedback scheduler and by categorizing the load as under load and overload, resulting in effective migration.
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