Optimizing resource utilization in cloud networks: An analysis of vm selection and placement policies

Cloud computing enables on-demand computing, providing users with elastic resources on a pay-as-you-go basis. The proliferation of data-driven applications and services has led to increased demand for computational resources, prompting the deployment of large data centers that consume significant amounts of energy and emit CO₂ into the environment. As VM placement and selection significantly impact energy consumption, this paper explores various benchmark algorithms for VM selection and placement policies, evaluating their performance based on SLA violations, energy consumption, and the number of migrations. The study utilizes the cloudsim toolkit and analyzes real workloads from the CoMon project.