Quantum Atlas-III Quantum Atlas-10K Seagate Barracuda Seagate Cheetah IBM 9ES in .NET

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Figure 5.13 Reduction in rebuild time versus media block size (N D = 5, = 0.5)
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800 Buffer Requirement (MB)
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Block-based Rebuild w/o Buffer Sharing Block-based Rebuild w/ Buffer Sharing Track-based Rebuild w/o Buffer Sharing Track-based Rebuild w/ Buffer Sharing Pipelined Rebuild
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Figure 5.14 Buffer requirement versus number of disks (Q = 64KB, Quantum Atlas-10K)
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108 Table 5.3 Buffer requirements (Q = 64KB, N D = 5) Quantum Atlas-III 107 MB 69 MB 182 MB 114 MB 70 MB
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Rebuild Algorithm Block-based rebuild w/o buffer sharing Block-based rebuild with buffer sharing Track-based rebuild w/o buffer sharing Track-based rebuild with buffer sharing Pipelined rebuild
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Quantum Atlas-10K 161 MB 104 MB 326 MB 222 MB 105 MB
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Seagate Barracuda 67 MB 43 MB 132 MB 89 MB 44 MB
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In addition to the rebuild algorithms studied in this chapter, there are also other techniques that may further improve rebuild performance. In particular, when serving active media streams in rebuild mode, the system has to recover lost data blocks for playback purpose. By storing these already reconstructed data blocks to the spare disk, one may be able to further shorten the rebuild time. However, storing individual data blocks to the spare disk might also adversely affect disk ef ciency in track-based rebuild. First, compared to track-based rebuild, more time is spent seeking rather than data transfer in block-based rebuild. Hence, the reduction in reading from the data disks is offset by the loss in disk ef ciency in the spare disk. Second, depending on the placement policy, rebuilding individual blocks may also require changes to the track-based rebuild algorithm as some tracks will have some of the blocks already reconstructed. Therefore, the performance impact is not obvious and more work is required to determine the applicability of such technique.
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References
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[1] F.A. Tobagi, J. Pang, R. Baird, and M. Gang, Streaming RAIDTM : A Disk Array Management System for Video Files, Proceedings of ACM Conference on Multimedia 93, Anaheium, CA, USA, Aug. 1993, pp. 393 400. [2] S. Berson, L. Golubchik, and R.R. Muntz, Fault Tolerant Design of Multimedia Servers, Proceedings of ACM SIGMOD International Conference on Management of Data, San Jose, CA, USA, May 1995, pp. 364 375. [3] A. Cohen, W.A. Burkhard, and P.V. Rangan, Pipelined Disk Arrays for Digital Movie Retrieval, Proc. of IEEE International Conference on Multimedia Computing and Systems, May 1995, pp. 312 317. [4] M.S. Chen, H.I. Hsiao, C.S. Li, and P.S. Yu, Using Rotational Mirrored Declustering for Replica Placement in a Disk-Array-Based Video Server, Proc. of ACM Multimedia 95, San Francisco, CA, USA, Nov. 1995. [5] B. Ozden, R. Rastogi, P. Shenoy, and A. Silberschatz, Fault-tolerant Architectures for Continuous-Media Servers, Proc. of ACM SIGMOD International Conference on Management of Data, Montreal, Canada, June 1996, pp. 79 90. [6] A.N. Mourad, Issues in the Design of a Storage Server for Video-on-Demand, ACM Multimedia Systems, vol. 4, April 1996, pp. 70 86. [7] A. Cohen and W.A. Burkhard, Segmented Information Dispersal (SID) for Ef cient Reconstruction in Faulttolerant Video Servers, Proc. of 4th ACM International Multimedia Conference, Boston, USA, Nov. 1996, pp. 227 286.
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Reliable and Fault-Tolerant Storage Systems
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[8] J. Korst, Random Duplicated Assignment: An Alternative to Striping in Video Servers, Proc. of the 5th ACM International Conference on Multimedia, Nov. 1997, pp. 219 226. [9] P. Chen, E. Lee, G. Gibson, R. Katz, and D. Patterson, RAID: High-Performance, Reliable Secondary Storage, ACM Computing Surveys, vol. 26, no. 2, June 1994, pp. 145 186. [10] J. Menon and D. Mattson, Performance of Disk Arrays in Transaction Processing Environments, Proc. of 12th International Conference on Distributed Computing Systems, June 1992, pp. 302 309. [11] J. Menon and D. Mattson, Distributed Sparing in Disk Arrays, Proc. of the 37th IEEE Computer Society International Conference, Compcon Spring 92, Feb 1992, pp. 410 421. [12] R.Y. Hou and Y.N. Patt, Comparing Rebuild Algorithms for Mirrored and RAID5 Disk Arrays, Proc. of the 1993 ACM SIGMOD International Conference on Management of Data, Washington, DC, USA, May 1993, pp. 317 326. [13] R.Y. Hou, J. Menon, and Y.N. Patt, Balancing I/O Response Time and Disk Rebuild Time in a RAID5 Disk Array, Proc. of the 26th Hawaii International Conference on System Sciences, Jan. 1993, pp. 70 79. [14] A. Thomasian, Performance Analysis of RAIDS Disk Arrays with a Vacationing Server Model for Rebuild Mode Operation, Proc. of the 10th International Conference on Data Engineering, Feb 1994, pp. 111 119. [15] A. Thomasian, Rebuild Options in RAID5 Disk Arrays, Proc. of the 7th IEEE Symposium on Parallel and Distributed Processing, Oct 1995, pp. 511 518. [16] A. Thomasian and J. Menon, RAID5 Performance with Distributed Sparing, IEEE Transactions on Parallel and Distributed Systems, vol. 8, no. 6, June 1997, pp. 640 657. [17] K. Mogi and M. Kitsuregawa, Hot Mirroring: A Method of Hiding Parity Update Penalty and Degradation During Rebuilds for RAID5, Proc. of the 1996 ACM SIGMOD International Conference on Management of Data, Montreal Canada, June 1996, pp. 183 194. [18] D.A. Patterson, G.A. Gibson, and R.H. Katz, A Case for Redundant Array of Inexpensive Disks (RAID), Proc. of the ACM Conference on Management of Data, June 1988, pp. 109 116. [19] A.L.N. Reddy and J.C. Wyllie, I/O Issues in a Multimedia System, IEEE Computer, vol. 27, no. 3, Mar 1994, pp. 69 74. [20] D.J. Gemmell, H.M. Vin, D.D. Kandlur, P.V. Rangan, and L.A. Rowe, Multimedia Storage Servers: A Tutorial, IEEE Computer, vol. 28, no. 5, May 1995, pp. 40 49. [21] G.R. Ganger, B.L. Worthington, and Y.N. Patt, The DiskSim Simulation Environment Version 2.0. http://www .ece.cmu.edu/ ganger/disksim.
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