Virtual I/O scheduler: a scheduler of schedulers for performance virtualization

Virtualized storage systems are required to service concurrently executing workloads, with potentially diverse data delivery requirements, that are running under multiple operating systems. Although a number of algorithms have been developed for I/O performance virtualization among operating system (OS) instances and their applications, none results in absolute performance virtualization. By absolute performance virtualization we mean that the performance experienced by applications of one operating system does not suffer due to variations in the I/O request stream characteristics of applications of other operating systems. Key requirements of I/O performance virtualization are fairness and performance isolation. In this paper, we present a novel virtual I/O scheduler (VIOS) that provides absolute performance virtualization by being fair in sharing I/O system resources among operating systems and their applications, and provides performance isolation in the face of variations in the characteristics of I/O streams. The VIOS controls the coarse grain allocation of disk time to the different operating system instances and is OS independent; optionally, a set of OS-dependent schedulers may determine the fine-grain interleaving of requests from the corresponding operating systems to the storage system.

[1]  Ravi Wijayaratne,et al.  Providing QOS guarantees for disk I/O , 2000, Multimedia Systems.

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

[3]  Robert Wisniewski.  relayfs : An Efficient Unified Approach for Transmitting Data from Kernel to User Space , 2003 .

[4]  D. Marr,et al.  Hyper-Threading Technology Architecture and MIcroarchitecture , 2002 .

[5]  Albert G. Greenberg,et al.  How fair is fair queuing , 1992, JACM.

[6]  Seetharami R. Seelam,et al.  Fairness and Performance Isolation: an Analysis of Disk Scheduling Algorithms , 2006, 2006 IEEE International Conference on Cluster Computing.

[7]  George Varghese,et al.  Efficient fair queueing using deficit round robin , 1995, SIGCOMM '95.

[8]  Micha Hofri.  Disk scheduling: FCFS vs.SSTF revisited , 1980, CACM.

[9]  Arif Merchant,et al.  Façade: Virtual Storage Devices with Performance Guarantees , 2003, FAST.

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

[11]  Toby J. Teorey,et al.  A comparative analysis of disk scheduling policies , 1972, CACM.

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

[13]  Paul E. McKenney,et al.  Stochastic fairness queueing , 1990, Proceedings. IEEE INFOCOM '90: Ninth Annual Joint Conference of the IEEE Computer and Communications Societies@m_The Multiple Facets of Integration.

[14]  Hewlett-Packard,et al.  Workload Dependent Performance Evaluation of the Linux 2 . 6 I / O Schedulers , 2004 .

[15]  Toby J. Teorey,et al.  A comparative analysis of disk scheduling policies , 1971, SOSP '71.

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

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

[18]  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.

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

[20]  S. Jamaloddin Golestani,et al.  A self-clocked fair queueing scheme for broadband applications , 1994, Proceedings of INFOCOM '94 Conference on Computer Communications.

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

[22]  John V. Guttag,et al.  Time-based Fairness Improves Performance in Multi-Rate WLANs , 2004, USENIX Annual Technical Conference, General Track.