Abstract
The growth in demand for using cloud computing resources at massive data centers has led to high consumption of energy and, consequently, increased operating costs. Integration of cloud resources makes it possible to save time on the migration of loaded and unprocessed data centers, to qualified data centers, the release of idle nodes, and the reduction of virtual machine virtualization migration.
One of the most important challenges is to choose the method of embedding virtual machines that are migrating to the node. Therefore, in this paper, a solution is proposed to reduce energy consumption in cloud data centers. In this solution, the gray wolf optimizer is used to properly assign the virtual machine to the appropriate node. The methodology was simulated with the Claudios software. The results of the simulation indicate a decrease in the number of virtual machines migrating, increasing the efficiency of migration and reducing energy consumption.
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Shahbazi, H., Jamshidi-Nejad, S. (2018). Smart Deployment of Virtual Machines to Reduce Energy Consumption of Cloud Computing Based Data Centers Using Gray Wolf Optimizer. In: Damaševičius, R., Vasiljevienė, G. (eds) Information and Software Technologies. ICIST 2018. Communications in Computer and Information Science, vol 920. Springer, Cham. https://doi.org/10.1007/978-3-319-99972-2_13
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