Energy-aware virtual machines allocation by krill herd algorithm in cloud data centers

The growing demand for computational power has led to the emergence of large-scale data centers that consume massive amounts of energy, thus resulting in high operating costs and CO2 emission. Furthermore, cloud computing environments are required to provide a high Quality of Service (QoS) to their clients and, therefore, need to handle power shortages. An optimized virtual machine allocation to physical hosts lowers energy consumption and allows for high-quality services. In this study, a novel solution was proposed for the allocation of virtual machines to physical hosts in cloud data centers using the Krill Herd algorithm, which is the fastest collective intelligence algorithm recently introduced. The performance of the proposed method was evaluated using the CloudSim simulator, and the results are suggestive of a 35% reduction in energy consumption.