Efficient QoS for Multi-Tiered Storage Systems

Multi-tiered storage systems using tiers of SSD and traditional hard disk is one of the fastest growing trends in the storage industry. Although using multiple tiers provides a flexible trade-off in terms of IOPS performance and storage capacity, we believe that providing performance isolation and QoS guarantees among various clients, gets significantly more challenging in such environments. Existing solutions focus mainly on either disk-based or SSD-based storage backends. In particular, the notion of IO cost that is used by existing solutions gets very hard to estimate or use. In this paper, we first argue that providing QoS in multi-tiered systems is quite challenging and existing solutions aren't good enough for such cases. To handle their drawbacks, we use a model of storage QoS called as reward scheduling and a corresponding algorithm, which favors the clients whose IOs are less costly on the back-end storage array for reasons such as better locality, read-mostly sequentiality, smaller working set as compared to SSD allocation etc. This allows for higher efficiency of the underlying system while providing desirable performance isolation. These results are validated using a simulation-based modeling of a multi-tiered storage system. We make a case that QoS in multi-tiered storage is an open problem and hope to encourage future research in this area.

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

[2]  Xiaoyun Zhu,et al.  Triage: Performance differentiation for storage systems using adaptive control , 2005, TOS.

[3]  William E. Weihl,et al.  Lottery scheduling: flexible proportional-share resource management , 1994, OSDI '94.

[4]  Ravi Wijayaratne,et al.  Integrated QOS management for disk I/O , 1999, Proceedings IEEE International Conference on Multimedia Computing and Systems.

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

[6]  Kai Shen,et al.  FIOS: a fair, efficient flash I/O scheduler , 2012, FAST.

[7]  Prashant J. Shenoy,et al.  Cello: A Disk Scheduling Framework for Bext Generation Operating Systems , 1998, SIGMETRICS.

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

[9]  Peter J. Varman,et al.  Brief announcement: application-sensitive QoS scheduling in storage servers , 2012, SPAA '12.

[10]  Analysis and Simulation of a Fair Queuing Algorithm , 2008 .

[11]  Peter J. Varman,et al.  mClock: Handling Throughput Variability for Hypervisor IO Scheduling , 2010, OSDI.

[12]  Irfan Ahmad,et al.  PARDA: Proportional Allocation of Resources for Distributed Storage Access , 2009, FAST.

[13]  Gregory R. Ganger,et al.  Towards higher disk head utilization: extracting free bandwidth from busy disk drives , 2000, OSDI.

[14]  Peter J. Varman,et al.  pClock: an arrival curve based approach for QoS guarantees in shared storage systems , 2007, SIGMETRICS '07.

[15]  Anand Sivasubramaniam,et al.  Storage performance virtualization via throughput and latency control , 2005, 13th IEEE International Symposium on Modeling, Analysis, and Simulation of Computer and Telecommunication Systems.

[16]  Fabio Checconi,et al.  High Throughput Disk Scheduling with Fair Bandwidth Distribution , 2010, IEEE Transactions on Computers.

[17]  Harrick M. Vin,et al.  Start-time fair queueing: a scheduling algorithm for integrated services packet switching networks , 1996, SIGCOMM '96.

[18]  Peter J. Varman,et al.  Reward Scheduling for QoS in Cloud Applications , 2012, 2012 12th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (ccgrid 2012).

[19]  Wei Jin,et al.  Interposed proportional sharing for a storage service utility , 2004, SIGMETRICS '04/Performance '04.

[20]  Gregory R. Ganger,et al.  Argon: Performance Insulation for Shared Storage Servers , 2007, FAST.

[21]  Carlos Maltzahn,et al.  Efficient guaranteed disk request scheduling with fahrrad , 2008, Eurosys '08.

[22]  Richard A. Golding,et al.  Zygaria: Storage Performance as a Managed Resource , 2006, 12th IEEE Real-Time and Embedded Technology and Applications Symposium (RTAS'06).