Energy-aware virtual machine allocation for cloud with resource reservation.

•We propose a novel fitness function based on our defined term instruction-energy ratio, which can effectively reduce the overall energy consumption and maximize the resource utilization of reservation-based cloud data centers.•Based on the evolutionary algorithm, we introduce a comprehensive VM allocation approach that can efficiently converge to a VM-to-PM mapping with best possible energy efficiency.•To further accelerate the exploration of optimal VM allocation solutions, we develop an efficient simulation engine and integrate it into the cloud simulator CloudSim, which can drastically reduce the evaluation time of VM allocation solutions in each evolutionary iteration.