Reloading Data from Back-up in VS .NET

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14.3 Reloading Data from Back-up
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If the media data in the system are also stored in a back-up storage, then we can simply load the required media data from the back-up media to the spare server. This can be done automatically without affecting the remaining active servers. The rebuild rate will then be equal to the transfer capacity of the back-up device or the spare server, whichever is smaller. While this scheme is simple and ef cient, the mechanisms needed to automate the process (selection and loading of media data) are not inexpensive, such as large juke-boxes or robotic tape libraries. Moreover, management of the back-up data will be more complex as old media data are removed and new ones uploaded to the servers from time to time. Finally, if the media data streams are backed up sequentially, then considerable searching will be needed when loading the media data into a spare server due to the server stripping scheme used. For comparison with other rebuild algorithms, we assume the back-up device has in nite throughput and capacity. Therefore, the rebuild rate is bounded by the server throughput, or Rreload = SS which is also the maximum rate that can be achieved by any data rebuild algorithm. (14.1)
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14.4 Baseline Rebuild
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The two methods discussed earlier both require extra hardware/software and/or human operator support. This section presents the rst automatic algorithm baseline rebuild, that requires neither extra hardware/software support nor human intervention. The principle is to utilize the idle capacities in the remaining servers to send data/redundant units to the spare server, which
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Algorithms for Server Rebuild
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S0 S1 S2 SN 1 Spare Server Ns 1
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Figure 14.5 The baseline rebuild algorithm
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then rebuilds the data lost in the failed server (Figure 14.5). This algorithm is similar to the baseline rebuild scheme in disk arrays [3]. To recover an unavailable data unit we need to perform erasure correction using the remaining (N S 1) data/redundant units. Since we want to keep the process transparent to normal streaming sessions, we can only utilize the servers idle capacities. Assuming the system is running at a utilization of [0,1], the average available transfer rate from each server will be equal to SS (1 ). The aggregate data transfer rate of the remaining (N S 1) servers is therefore equal to r = SS (1 )(N S 1) (14.2)
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Now as the spare server has a transfer capacity of SS , the aggregate data rate r will exceed the spare server s transfer capacity if is less than (1 /(N S 1)). This is stated in the Theorem 14.1 which computes the upper limit on the baseline rebuild rate. Theorem 14.1. The data rebuild rate of baseline rebuild, denoted by Rbaseline is bounded by the capacity S S of the spare server and is given by Rbaseline = SS /(N S 1) for < (1 1/(N S 1)) SS (1 ) for (1 1/(N S 1)) (14.3)
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Proof. Case 1: < (1 1/(N S 1)) From equation (14.2): r = SS (1 )(N S 1) SS (1 (1 1/(N S 1)))(N S 1) = SS
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Although the aggregate transfer rate from the remaining servers is greater than SS , the spare server can only accept data at a rate of SS . Using erasure correction the spare server will rebuild one data unit for every (N S 1) data/redundant units received. We have therefore a rebuild rate Rbaseline = SS /(N S 1) at the spare server. Case 2: (1 1/(N S 1)) From equation (14.2): r = SS (1 )(N S 1) SS (1 (1 1/(N S 1)))(N S 1) = SS As the transfer rate from the remaining servers is less than SS , the corresponding rebuild rate at the spare server is Rbaseline = r/ (N S 1) = SS (1 ). The rebuild time for a server with storage U is then given by Tbaseline = (N S 1)U min {SS , SS (1 )(N S 1)} (14.4)
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