A multicore periodical preemption virtual machine scheduling scheme to improve the performance of computational tasks

In virtualized environments, the VMM (virtual machine monitor) scheduler is critical to overall performance, as it allocates the physical resources. However, traditional schedulers have poor I/O performance of mixed workloads. Although recent research significantly improves I/O performance, they degrade the performance of computational tasks by shortening time slices and reducing cache efficiency. In order to eliminate these problems while guaranteeing I/O performance, this paper presents a multicore periodical preemption scheduling scheme with three optimization techniques: (1) periodically coalescing and handling I/O events to reduce the preemption rate and scheduling latency, which guarantees I/O performance; (2) taking advantage of multicore environments and centrally handling I/O events on different cores in a Round-Robin manner to lengthen time slices, which improves the performance of computational tasks; (3) using a dedicated priority for I/O event handling to keep the CPU fairness. We implement a Xen-based prototype and evaluate the performance of I/O workloads and computation-intensive workloads. The experimental results demonstrate that our scheduling scheme efficiently lengthens time slices and improves the performance of computational tasks, achieving the same I/O performance as the existing approaches optimized for I/O.