Spatial Locality Aware Disk Scheduling in Virtualized Environment

摘要

Exploiting spatial locality, a key technique for improving disk I/O utilization and performance, faces additional challenges in the virtualized cloud because of the transparency feature of virtualization. This paper contributes a novel disk I/O scheduling framework, named Pregather, to improve disk I/O efficiency through exposure and exploitation of the special spatial locality in the virtualized environment, thereby improving the performance of disk-intensive applications without harming the transparency feature of virtualization. The key idea behind is to implement an intelligent model to predict the access regularity of spatial locality for each VM. Moreover, embraces an adaptive time slice allocation scheme to further reduce the resource contention and ensure fairness among VMs. We implement the disk scheduling framework and perform extensive experiments that involve multiple simultaneous applications of both synthetic benchmarks and MapReduce applications on Xen-based platforms. Our experiments demonstrate the accuracy of our prediction model and indicate that results in the high disk spatial locality and a significant improvement in disk throughput and application performance.