Façade: Virtual Storage Devices with Performance Guarantees

High-end storage systems, such as those in large data centers, must service multiple independent workloads. Workloads often require predictable quality of service, despite the fact that they have to compete with other rapidly-changing workloads for access to common storage resources. We present a novel approach to providing performance guarantees in this highly-volatile scenario, in an efficient and cost-effective way. Facade, a virtual store controller, sits between hosts and storage devices in the network, and throttles individual I/O requests from multiple clients so that devices do not saturate. We implemented a prototype, and evaluated it using real workloads on an enterprise storage system. We also instantiated it to the particular case of emulating commercial disk arrays. Our results show that Facade satisfies performance objectives while making efficient use of the storage resources--even in the presence of of failures and bursty workloads with stringent performance requirements.

[1]  John Nagle,et al.  On Packet Switches with Infinite Storage , 1985, IEEE Trans. Commun..

[2]  Scott Shenker,et al.  Analysis and simulation of a fair queueing algorithm , 1989, SIGCOMM '89.

[3]  P. Venkat Rangan,et al.  Multimedia Storage Servers: A Tutorial , 1995, Computer.

[4]  Carl Staelin,et al.  The HP AutoRAID hierarchical storage system , 1995, SOSP.

[5]  Tom Madell,et al.  Disk and file management tasks on HP-UX , 1996 .

[6]  Harrick M. Vin,et al.  Generalized guaranteed rate scheduling algorithms: a framework , 1997, TNET.

[7]  Zheng Wang,et al.  An Architecture for Differentiated Services , 1998, RFC.

[8]  Andrew T. Campbell,et al.  A survey of QoS architectures , 1998, Multimedia Systems.

[9]  David L. Black,et al.  An Architecture for Differentiated Service , 1998 .

[10]  Prashant J. Shenoy,et al.  Cello: A Disk Scheduling Framework for Next Generation Operating Systems* , 1998, SIGMETRICS '98/PERFORMANCE '98.

[11]  Banu Özden,et al.  Disk scheduling with quality of service guarantees , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

[12]  Margo I. Seltzer,et al.  Isolation with Flexibility: A Resource Management Framework for Central Servers , 2000, USENIX Annual Technical Conference, General Track.

[13]  John Wilkes,et al.  Traveling to Rome: QoS Specifications for Automated Storage System Management , 2001, IWQoS.

[14]  Nicolas Christin,et al.  The QoSbox: A PC-Router for Quantitative Service Differentiation in IP Networks , 2001 .

[15]  Arif Merchant,et al.  Minerva: An automated resource provisioning tool for large-scale storage systems , 2001, TOCS.

[16]  Eric Anderson,et al.  Proceedings of the Fast 2002 Conference on File and Storage Technologies Hippodrome: Running Circles around Storage Administration , 2022 .

[17]  Giorgio C. Buttazzo,et al.  Adaptive Workload Management through Elastic Scheduling , 2002, Real-Time Systems.