Alper KizilKorhan Karabulut2025-10-0620241300-188410.17341/gazimmfd.1202336http://dx.doi.org/10.17341/gazimmfd.1202336https://gcris.yasar.edu.tr/handle/123456789/6277Cloud computing is a newly emerging computing concept that is only strengthened by the advent ofworldwide internet infrastructure. Although these datacenters are giant have a limited set of resources andpotentially infinite demand for these resources and these resources needed to be mapped that is most cost effective and time efficient. This problem is known in literature as cloud resource scheduling problem andit is proven to be NP-Hard. This study proposes two genetic algorithm-based solvers that will work on the VM Task assignment level and try to optimize makespan and energy consumption while assigning these user tasks and tries to determine if there is a tradeoff between these two metrics in different host loads (different number of VMs per host machine). Figure A explains how the proposed system is going to work. Users in the system submit their jobs in the form of tasks. These tasks are then assigned to virtual machines running on physical server machines by the proposed 2 genetic algorithms.EnglishEnergy Consumption, Makespan, Genetic Algorithm, Task SchedulingGENETIC ALGORITHMArticle