Authors: Sergey Artyomovich Mamedov, Yelena Ramizovna Isayeva, Anar Fikret oglu Mahmudov, Kamilla Rauf qizi Veliyeva
Abstract: Biomedical data centers serve as the backbone of modern healthcare analytics, precision medicine, and hospital informatics. As the volume of healthcare data surges, the need for scalable, secure, and efficient computing infrastructure becomes paramount. Server virtualization has emerged as a critical enabler in this space, offering resource abstraction, fault tolerance, and operational flexibility. This study performs a comparative assessment of leading server virtualization techniques—namely hypervisor-based (e.g., KVM, VMware ESXi), container-based (e.g., Docker, LXC), and hybrid models—based on key parameters such as performance, scalability, resource utilization, latency, and compliance with biomedical data handling norms. Benchmarks using real-world datasets, including EHRs and PACS workloads, reveal that no single approach dominates across all metrics, emphasizing the need for context-driven infrastructure design.
DOI: https://doi.org/10.5281/zenodo.16314536
