SDFS: A software‐defined file system for multitenant cloud storage

Abstract

Performance isolation is highly desirable in cloud platforms where the virtual disks of virtual machines are simply large files on the shared and networked storage servers. However, existing isolation techniques cannot deal with the implications of the file system used by the networked storage servers, such that underlying resource usage is unpredictable (eg, the delayed write-back mechanism could postpone writes, and the journaling mechanism could amplify writes). The lack of visibility on underlying resource usage leads to the predicament of being unable to meet isolation goals. In this paper, we present a software-defined file system (SDFS) that exploits the underlying file system to allocate resources at per-image-file granularity and provide tenants with guaranteed throughput. The SDFS comprises two components: control plane and data plane. At the control plane, we provide a set of system calls to document tenant performance requirements into the metadata of image files. At the data plane, we construct a file-based scheduler to manage memory and disk resources according to the tenant performance requirements. The SDFS design does not require a modification to guest operating systems, hypervisors, or file server protocols. Through a prototype implementation, we demonstrate that the SDFS can meet isolation goals and increase resource utilization with negligible overhead.

TOSDS: Tenant-centric Object-based Software Defined Storage for Multitenant SaaS Applications

“…Virtual machines in a cloud platform store data in the form of large files on networked storage servers [ 25 ]. Software-defined file system (SDFS) is been proposed to provide performance isolation by allocating resources at per-image-file granularity.…”