A Linux-based virtual desktop system leveraging containerization technology to address inefficiencies of conventional VDI solutions, highlighting the advantages of containerization in virtual desktop systems, particularly with respect to resource efficiency, scalability, energy conservation, and user experience under on-demand deployment scenarios.
Abstract
Virtual Desktop Infrastructure (VDI) has emerged as a mature and widely adopted technology within the domain of cloud computing. Despite its advantages, conventional VDI solutions predominantly rely on hardware-level virtualization as the underlying backend technology, resulting in relatively high resource consumption. In this study, we propose and develop a Linux-based virtual desktop system leveraging containerization technology to address these inefficiencies. The proposed system facilitates rapid provisioning of virtual desktop environments while centralizing authenticated access through a unified network entry point. Furthermore, support for multi-cluster deployment enhances management flexibility and scalability, enabling horizontal expansion as demand increases. Empirical evaluations demonstrate that, in comparison to KVM-based virtual machines with both full-disk cloning and copy-on-write (qcow2) configurations on identical hardware, container-based deployment achieves substantial reductions in resource utilization—specifically, a 71.3% decrease in memory consumption and a 99.8% reduction in storage usage per deployed instance. Additionally, the average power draw is reduced to 58.0%, and the provisioning time is significantly shortened from 42.5 seconds to merely 2.5 seconds. A regression-based analysis further identifies the deployment scale—approximately 20 to 25 concurrent desktops—beyond which the containerized back-end becomes more efficient than the VM baselines, yielding a simple decision model for practitioners. These findings underscore the advantages of containerization in virtual desktop systems, particularly with respect to resource efficiency, scalability, energy conservation, and user experience under on-demand deployment scenarios.
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