One of the mechanisms to achieve energy efficiency in virtualized/cloud environments is consolidation of workloads on an optimal number of servers and switching-off of idle or underutilized servers. Central to this approach is the migration of virtual machines at runtime. In this paper we investigate the cost (migration time) of virtual machines migration. We shall show that migration time exponentially increases as the available network bandwidth decreases; migration time linearly increases as

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... the RAM size of a virtual machine increases. Furthermore, the power consumption of both the destination and the source servers remain by and large the same for a fixed network bandwidth, regardless of the VM size. Interestingly, for the same combination of virtual machines, different orders of migrations resulted in different migration time. We observed that migrating resource intensive virtual machines first yields the shortest migration time. In general, the migration time should be modeled as a random variable since the factors that affect it cannot be known except in a probabilistic sense. Therefore, we propose a probabilistic approach to quantify the cost of virtual machines migration.