vFair: latency-aware fair storage scheduling via per-IO cost-based differentiation

Abstract

In virtualized data centers, multiple VMs are consolidated to access a shared storage system. Effective storage resource management, however, turns out to be challenging, as VM workloads exhibit various IO patterns and diverse loads. To multiplex the underlying hardware resources among VMs, providing fairness and isolation while maintaining high resource utilization becomes imperative for effective storage resource management. Existing schedulers such as Linux CFQ or SFQ can provide some fairness, but it has been observed that synchronous IO tends to lose fair shares significantly when competing with aggressive VMs. In this paper, we introduce vFair, a novel scheduling framework that achieves IO resource sharing fairness among VMs, regardless of their IO patterns and workloads. The design of vFair takes per-IO cost into consideration and strikes a balance between fairness and storage resource utilization. We have developed a Xen-based prototype of vFair and evaluated it with a wide range of storage workloads. Our results from both micro-benchmarks and real-world applications demonstrate the effectiveness of vFair, with significantly improved fairness and high resource utilization.