A novel disk I/O scheduling framework of virtualized storage system

Modern data centers usually use virtual machine technology to host various big data applications in a single physical machine, not only enhancing the server utilization, but also providing them with the hardware-level isolation. However, in a typical virtualized environment an extra software layer called virtual machine monitor (VMM) is often interposed between the hardware resource and guest operating system (virtual machine, VM), shielding the specific user-process semantic inside a running VM. As a result, it obstructs the disk I/O scheduler of VMM to acquire the accurate information of a user-process (often a big data application), and thus proposes a challenge on the I/O request scheduling as well as the disk resource management at the granularity of VM user-process. Eventually, the disk I/O performance of a virtualized system is sub-optimal. This paper introduces an improved disk I/O scheduling framework for the virtualized system. It aims at bridging the semantic gap between physical disk I/O scheduler and VM user-process, providing a fair sharing of disk I/O resource among concurrent VMs. At the same time, it improves the overall disk I/O performance through a novel method for creating the image file of VM. Besides, an extra scheduling algorithm is proposed to further refine the storage performance. Finally, we implement these improvements on Xen hypervisor and conduct extensive experiments to verify our framework. The experimental result shows that our work improve the performance of read-intensive, write-intensive and mixed workloads up to 9, 10.7 and 20% respectively.