The paper introduces a flexible architecture for Virtual Desktop Infrastructure (VDI), focusing on quality of service (QoS) control through a unique image compression method utilizing k-means clustering for 2D images. This approach significantly reduces the size of transmitted video data while maintaining quality. Additionally, it integrates a model for estimating optimal streaming policies, leveraging historical data and linear regression analysis to enhance user experience. Experimental results demonstrate the effectiveness of the proposed system, outperforming existing methods and indicating potential for further research in related areas.
This paper presented a new architecture with flexible QoS control for Virtual Desktop Infrastructure, utilizing a novel compression method for 2D images based on k-means clustering.
Using simulations with a real-world dataset, the paper demonstrates the effectiveness of their approach in outpacing previously reported methods in terms of QoS.
To boost users' quality of experience, we incorporated a model to estimate optimal streaming policies by analyzing historical data through linear regression modeling.
The proposed architecture is poised to open significant pathways for future research in the realm of Virtual Desktop Infrastructure and quality of service improvements.
#virtual-desktop-infrastructure #image-compression #quality-of-service #k-means-clustering #qoe-improvement
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