Split-level I/O scheduling
Suli Yang, Tyler Harter, Nishant Agrawal, Salini Selvaraj Kowsalya, Anand Krishnamurthy, Samer Al-Kiswany, Rini T. Kaushik, Andrea Carol Arpaci-Dusseau, Remzi H. Arpaci-Dusseau · 2015
We introduce split-level I/O scheduling, a new framework that splits I/O scheduling logic across handlers at three layers of the storage stack: block, system call, and page cache. We demonstrate that traditional block-level I/O schedulers are unable to meet throughput, latency, and isolation goals. By utilizing the split-level framework, we build a variety of novel schedulers to readily achieve these goals: our Actually Fair Queuing scheduler reduces priority-misallocation by 28x; our Split-Deadline scheduler reduces tail latencies by 4x; our Split-Token scheduler reduces sensitivity to interference by 6x. We show that the framework is general and operates correctly with disparate file systems (ext4 and XFS). Finally, we demonstrate that split-level scheduling serves as a useful foundation for databases (SQLite and PostgreSQL), hypervisors (QEMU), and distributed file systems (HDFS), delivering improved isolation and performance in these important application scenarios.