PCOS: Prescient Cloud I/O Scheduler for Workload Consolidation and Performance

Server consolidation is at the heart of Cloud computing paradigm. Applications running on Cloud exhibit a broad spectrum of functionality, having varied characteristics and resource requirements. An optimal combination of concurrent applications on a server can enable maximum resource utilization of the physical resources while also ensuring the desired performance. In this work, we analyze the need for meta-scheduling of I/O workloads in Cloud computing environments in the context of disk consolidation and I/O performance. We propose a proactive admission controller and disk scheduling framework PCOS for I/O intensive applications. By foreseeing the resource utilization patterns of the applications while scheduling new requests on a server, PCOS enables the selection of suitable workload combination for servers to optimize disk bandwidth utilization. At the same time, PCOS can guarantee that performance is not adversely affected by scheduling of new I/O requests on the server. Experimental validations performed on real world I/O traces demonstrate the utility and importance of this framework for actual Cloud storage environments.