Abstract
We present a new disk scheduling framework to address the needs of a shared multimedia service that provides differentiated multilevel quality-of-service for mixed-media workloads. In such a shared service, requests from different users have different associated performance objectives and utilities, in accordance with the negotiated service-level agreements (SLAs). Service providers typically provision resources only for average workload intensity, so it becomes important to handle workload surges in a way that maximizes the utility of the served requests.
We capture the performance objectives and utilities associated with these multiclass diverse workloads in a unified framework and formulate the disk scheduling problem as a reward maximization problem. We map the reward maximization problem to a minimization problem on graphs and, by novel use of graph-theoretic techniques, design a scheduling algorithm that is computationally efficient and optimal in the class of seek-optimizing algorithms. Comprehensive experimental studies demonstrate that the proposed algorithm outperforms other disk schedulers under all loads, with the performance improvement approaching 100% under certain high load conditions. In contrast to existing schedulers, the proposed scheduler is extensible to new performance objectives (workload type) and utilities by simply altering the reward functions associated with the requests.
- Aggarwal, G., Dubey, P. K., Ghosal, S., Kulshreshtha, A., and Sarkar, A. 2000. iPURE: Perceptual and user-friendly retrieval of images. In the IEEE International Conference on Multimedia and Expo (ICME).Google Scholar
- Andrews, M., Bender, M. A., and Zang, L. 2002. New algorithms for the disk scheduling problem. Algorithmica 32, 2, 277--301.Google Scholar
Digital Library
- Bruno, J., Brustoloni, J., Gabber, E., Ozden, B., and Silberschatz, A. 1999. Disk scheduling with quality of service guarantees. In Proceedings of the International Conference on Multimedia Computing and Systems. Google Scholar
Digital Library
- Chase, J. S., Anderson, D., Thakar, P., Vahdat, A., and Doyle, R. 2001. Managing energy and server resources in hosting centers. In the 18th Symposium on Operating Systems Principles (SOSP). Google Scholar
Digital Library
- Chen, S., Stankovic, J. A., Kurose, J. F., and Towsley, D. 1991. Performance evaluation of two new disk scheduling algorithms for real-time systems. J. Real-Time Syst. 3, 307--336.Google Scholar
Cross Ref
- Dasgupta, K., Ghosal, S., Jain, R., Sharma, U., and Verma, A. 2005. QoSMig: Adaptive rate-controlled migration of bulk data in storage systems. In the International Conference on Data Engineering. Google Scholar
Digital Library
- Department of Distributed Systems. 2007. Index of MPEG traces. http://www3.informatik. uni-wuerzburg.de/MPEG/traces.Google Scholar
- Ganger, G. R., Worthington, B. L., and Patt, Y. N. 1999. The DiskSim simulation environment: Version 2.0 reference manual. Tech. Rep. CSE-TR-358-98, Department of Electrical Engineering and Computer Science, University of Michigan.Google Scholar
- Ghandeharizadeh, S., Huang, L., and Kamel, A. 2003. A cost driven disk scheduling algorithm for multimedia object retrieval. IEEE Trans. Multimedia 5, 2, 186--196. Google Scholar
Digital Library
- Gallo, G., Malucelli, F., and Marre, M. 1995. Hamiltonian paths algorithms for disk scheduling. Tech. Rep. HPL-95-71, HP Labs.Google Scholar
- Hsu, W. W. and Smith, A. J. 2003. Characteristics of I/O traffic in personal computer and server workloads. IBM Syst. J. 42, 2, 347--372. Google Scholar
Digital Library
- Huang, L. and Chiueh, T. 2002. Experiences in building a software-based SATF scheduler. Tech. Rep., State University of New York at StonyBrook, July.Google Scholar
- Huang, L., Peng, G., and Chiueh, T. 2004. Multi-Dimensional storage virtualization. In Proceedings of the ACM SIGMETRICS Joint International Conference on Measurement and Modeling of Computer Systems. Google Scholar
Digital Library
- Iyengar, A. K., Squillante, M. S., and Zhang, L. 1999. Analysis and characterization of large-scale web server access patterns and performance. In Proceedings of the International World Wide Web Conference. Google Scholar
Digital Library
- Irwin, D., Chase, J. S., and Grit, L. E. 2004. Balancing risk and reward in market-based task scheduling. In Proceedings of the 13th International Symposium on High-Performance Distributed Computing. Google Scholar
Digital Library
- Jin, W., Chase, J. S., and Kaur, J. 2004. Access method concurrency with recovery. In Proceedings of the ACM Conference on Electronic Commerce (EC), 213--223.Google Scholar
- Liu, Z., Squillante, M. S., and Wolf, J. L. 2001. On maximizing service level agreement profits.ACM Trans. Comput. Syst.Google Scholar
- Lumb, C., Merchant, A., and Alvarez, G. A. 2003. Façade: Virtual storage devices with performance guarantees. In Proceedings of the USENIX Conference on File and Storage Technologies (FAST). Google Scholar
Digital Library
- Lund, K. and Goebel, V. 2003. Adaptive disk scheduling in a multimedia DBMS. In Proceedings of the ACM International Multimedia Conference, 65--74. Google Scholar
Digital Library
- Mokbel, M. F., Aref, W. G., El-Bassyouni, K., and Kamel, I. 2005. Scalable multimedia disk scheduling. In the International Conference on Data Engineering. Google Scholar
Digital Library
- Papadimitriou, C. H. 1977. The Euclidean traveling salesman problem is NP-complete. Theor. Comput. Sci. 4, 237--244.Google Scholar
Cross Ref
- PC Technology Guide. 2004. Storage-Hard disks. http://www.pctechguide.com/04disks.htm.Google Scholar
- PC Technology Guide. 2002. Components-Processors. http://www.pctechguide.com/02procs.htm.Google Scholar
- Popovici, F. I., Arpaci-Dusseau, A. C., and Arpaci-Dusseau, R. H. 2003. Robust, portable I/O scheduling with the disk mimic. In Proceedings of the USENIX Annual Technical Conference, 297--310.Google Scholar
- Reddy, A. N. and Wyllie, J. 1993. Disk scheduling in multimedia I/O system. In Proceedings of the ACM Multimedia Conference, 225--234. Google Scholar
Digital Library
- Romopogiannakis, Y., Nerjes, G., Muth, P., Paterakis, M., Triantafillou, P., and Weikum, G. 1998. Disk scheduling for mixed-media workloads in a multimedia server. In Proceedings of the ACM Multimedia Conference. Google Scholar
Digital Library
- Schindler, J. and Ganger, G. R. 1999. Automated disk drive characterization. Tech. Rep. CMU-CS-99-176, Carnegie Mellon University, December.Google Scholar
- Schindler, J., Griffin, J. L., Lumb, C. R., and Ganger, G. R. 2002. Track-Aligned extents: Matching access patterns to disk drive characteristics. In the USENIX Conference on File and Storage Technologies (FAST). Google Scholar
Digital Library
- Seagate Corporation. 2007. Cheetah4LP disk specification datasheet. http://www.seagate.com.Google Scholar
- Seltzer, M., Chen, P., and Ousterhout, J. 1990. Disk scheduling revisited. In Proceedings of the USENIX Winter Technical Conference, 313--324.Google Scholar
- Shenoy, P. and Vin, H. M. 1999. Efficient support for interactive operations in multi-resolution video servers. Multimedia Syst. 7, 241--253. Google Scholar
Digital Library
- Shenoy, P. and Vin, H. M. 1998. Cello: A disk scheduling framework for next generation operating systems. In Proceedings of the ACM SIGMETRICS Joint International Conference on Measurement and Modeling of Computer Systems, 44--55. Google Scholar
Digital Library
- Verma, A. and Ghosal, S. 2003. Online admission control for profit maximization of networked service providers. In Proceedings of the World Wide Web Conference, 128--137. Google Scholar
Digital Library
Index Terms
A utility-based unified disk scheduling framework for shared mixed-media services
Recommendations
A heuristic-based real-time disk scheduling algorithm for mixed-media workload
IMSA'06: Proceedings of the 24th IASTED international conference on Internet and multimedia systems and applicationsFor mixed-media workload, disk scheduling strategies should meet the deadlines of requests with timing constraints while optimizing the disk utilization. To design a scheduling algorithm in mixed-media workload environment is very intricate because ...
Performance Comparison of Mirrored Disk Scheduling Methods with a Shared Non-Volatile Cache
Mirrored disks or RAID1 is a popular disk array paradigm, which in addition to fault-tolerance, doubles the data access bandwidth. This is important in view of rapidly increasing disk capacities and the slow improvement in disk access time. Caching of ...
Mirrored disk rouing and scheduling
Disk mirroring or RAID level 1 stores the same data twice, on two independent disks, to ensure that all single disk failures can be tolerated. This high storage overhead is acceptable in view of the drop in storage cost per gigabyte and rapidly ...






Comments