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

• Apeksha Bhuekar

  Author

Virtual machine (VM) placement plays a critical role in improving resource utilisation, reducing operational costs, and maintaining Service Level Agreement (SLA) compliance in cloud computing environments. However, evaluating VM placement algorithms in real infrastructures is often expensive, time-consuming, and difficult to reproduce at scale. This paper presents VMPlaceS (VMPS), a high-fidelity simulation framework built on SimGrid for the development, testing, and comparative analysis of dynamic VM placement strategies. VMPS provides a configurable environment for modelling large-scale cloud infrastructures, dynamic workloads, VM migrations, and resource contention while supporting reproducible experimentation through synthetic workload generation. The framework incorporates an event-driven architecture consisting of initialisation, workload injection, and trace analysis phases, enabling detailed monitoring of system behaviour and algorithm performance. To demonstrate its capabilities, three representative placement approaches are implemented and evaluated: the centralised Entropy algorithm, the hierarchical Snooze framework, and the distributed DVMS strategy. Experimental results show that VMPS closely reproduces real-world behaviour, with simulation outcomes differing from in-vivo executions by a median of approximately 12%. Scalability studies further indicate that distributed placement approaches achieve superior responsiveness and lower violation times in large-scale environments. The proposed framework provides researchers and practitioners with a practical and extensible platform for evaluating VM placement solutions under realistic cloud conditions.

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