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A utility-based unified disk scheduling framework for shared mixed-media services
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ACM Transactions on Storage (TOS) archive
Volume 3 ,  Issue 4  (February 2008) table of contents
Article No. 4  
Year of Publication: 2008
ISSN:1553-3077
Authors
Akshat Verma  IBM India Research Lab, New Delhi, India
Rohit Jain  IBM India Research Lab, New Delhi, India
Sugata Ghosal  IBM India Research Lab, New Delhi, India
Publisher
ACM  New York, NY, USA
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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.


REFERENCES

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1
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).
 
2
Andrews, M., Bender, M. A., and Zang, L. 2002. New algorithms for the disk scheduling problem. Algorithmica 32, 2, 277--301.
 
3
4
 
5
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.
 
6
 
7
Department of Distributed Systems. 2007. Index of MPEG traces. http://www3.informatik. uni-wuerzburg.de/MPEG/traces.
 
8
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.
 
9
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.
 
10
Gallo, G., Malucelli, F., and Marre, M. 1995. Hamiltonian paths algorithms for disk scheduling. Tech. Rep. HPL-95-71, HP Labs.
 
11
 
12
Huang, L. and Chiueh, T. 2002. Experiences in building a software-based SATF scheduler. Tech. Rep., State University of New York at StonyBrook, July.
13
 
14
 
15
 
16
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.
 
17
Liu, Z., Squillante, M. S., and Wolf, J. L. 2001. On maximizing service level agreement profits.ACM Trans. Comput. Syst.
 
18
19
 
20
 
21
Papadimitriou, C. H. 1977. The Euclidean traveling salesman problem is NP-complete. Theor. Comput. Sci. 4, 237--244.
 
22
PC Technology Guide. 2004. Storage-Hard disks. http://www.pctechguide.com/04disks.htm.
 
23
PC Technology Guide. 2002. Components-Processors. http://www.pctechguide.com/02procs.htm.
 
24
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.
25
26
 
27
Schindler, J. and Ganger, G. R. 1999. Automated disk drive characterization. Tech. Rep. CMU-CS-99-176, Carnegie Mellon University, December.
 
28
 
29
Seagate Corporation. 2007. Cheetah4LP disk specification datasheet. http://www.seagate.com.
 
30
Seltzer, M., Chen, P., and Ousterhout, J. 1990. Disk scheduling revisited. In Proceedings of the USENIX Winter Technical Conference, 313--324.
 
31
32
33

Collaborative Colleagues:
Akshat Verma: colleagues
Rohit Jain: colleagues
Sugata Ghosal: colleagues