Improved sparrow algorithm based virtual machine placement

To mitigate severe physical resource consumption in cloud data centers, we propose an Improved Sparrow Search Algorithm-Based Virtual Machine Placement (ISSA-VMP) method. Incorporating Chebyshev chaotic mapping and Levy flight disturbance enhances resource allocation diversity in the search space. The mapping encoding scheme transforms virtual machine placement solutions into continuous positional information. ISSA-VMP establishes a cloud data center resource consumption model to maximize physical host resource utilization efficiency. The simulation results demonstrate the excellent performance of ISSA-VMP in virtual machine migration and physical resource utilization, significantly reducing task completion time. Compared to the best performing algorithm, the execution rate has increased by 5.57–18.11%. ISSA-VMP achieves high and stable physical resource utilization rates, ensuring efficient utilization, with a stable Service Level Agreement (SLA) violation rate. In summary, ISSA-VMP is a promising, efficient solution for optimizing resource allocation in cloud data centers.