RT-VirtIO: Towards the Real-Time Performance of VirtIO in a Two-Tier Computing Architecture

With the popularity of virtualization technology, ensuring reliable I/O operations with timing constraints in virtual environments becomes increasingly critical. Timing-predictable virtual I/O enhances the responsiveness and efficiency of virtualized systems, facilitating their seamless integration into time-critical applications such as industrial automation and robotics. Its significance lies in meeting rigorous performance standards, minimizing latency, and consistently delivering predictable I/O performance. As a result, virtual machines can effectively support mission-critical and time-sensitive workloads. However, due to the complicated system architecture, the I/O operations in virtualization face competition from tasks within the same virtual machine and those in different virtual machines who share the same host machine. This study presents RT-VirtIO, a practical approach to provide predictable real-time I/O operations. RT-VirtIO addresses the challenges associated with lengthy data paths and complex resource management. Through early-stage characterization, this study identifies key factors contributing to poor I/O real-time performance and then builds an analytical model and a learning-based data-driven model to predict the tail I/O latency. Leveraging these two models, RT-VirtIO effectively captures these dynamics, enabling the development of a general and applicable optimization framework. Experimental results demonstrate that RT-VirtIO significantly improves real-time performance in virtual environments (by 20.07% ~ 30.90%) without necessitating hardware modifications, which exhibit promising applicability across a broader range of scenarios.