VMPlaceS Enables Scalable Evaluation of Virtual Machine Placement Strategies Using a High-Fidelity Simulation Framework

Efficient placement of Virtual Machines (VMs) iscritical for optimizing resource utilization and ensuring servicereliability in cloud computing infrastructures. Existing validationmethods for VM placement algorithms, such as limited in-vivoexperiments and ad hoc simulators, often fail to reflect real-worldcomplexities and provide fair comparisons. This paper introducesVMPlaceS, a simulation framework built on SimGrid, designed toaddress these shortcomings by enabling the robust evaluation andcomparison of VM placement strategies. VMPlaceS facilitateslarge-scale scenario modeling with customizable parameters torepresent dynamic workloads and realistic platform conditions.By simulating centralized, hierarchical, and distributed algo-rithms, this study highlights the framework’s capability to assessscalability, reactivity, and SLA adherence in various deploymentscenarios. VMPlaceS emerges as a valuable tool for researchersand practitioners to explore innovative VM placement solutionsand advance the field of cloud computing resource management.