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Zk is a Poisson random variable with mean lk. If J does not depend on z, then Var xi const. Let us take J such that lExi > m d1 for z > J and z > d2 =J m d1 . By the strong law of large numbers

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1 minfSk k!1



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This process is called OCR (Optical Character Recognition). ... to scanning with Image Capture, you can download and install Epson Scan scanning software.

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had been canceled, and StubHub denied fans requests for refunds, on the grounds that the game had actually been played. But after spotting trouble brewing online, the company offered discounts and credits to the affected fans. It is now re-evaluating its bad weather policy. This is a canary in a coal mine for us, said John Whelan, StubHub s director of customer service. (www.nytimes.com/2009/ 08/24/technology/internet/24emotion.html)

k m d1 g > zd2 1: 8:41

1 (Thursday s full)

Now we will nd the second probability in the inequality (8.40). We have Pr where n 2 max 0; n 2 Yt 2 C d1 m : t t 1 Next, Prfn 2 > z 1 d2 g ! t

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Download FreeOCR. FreeOCR is Optical Character Recognition Software for Windows and supports scanning from most Twain scanners and can also open ...

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l Prft0;1 lg l 1 a1 z 1 d2 = 1 a1 ; where li gi l, g > 1, m1 C d1 m 1, and a1 C d1 m m1 1. Putting g 1 2=bm1 we get Prfn 2 > z 1 d2 g ! t bm1 m1 1 =2 1 a1 bm1 bm1 1 b m1 1 bm1 1 bm1 2 bm1 m1 1 2 lc0 m1 z 1 d2 bm1 o z bm1 : 8:42 2 bm1

When selecting the method that is best for you, you must strike a balance between the duration of your backups, which are probably nightly events, and the duration and effort required to perform a complete restore. Complete restores may only be required once or twice a year. But the duration of the restore is your MTTR. As we have said so many times before, you want to keep your MTTRs as low as possible, as some portion of your system is out of service until the effort is completed.

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Taking d1 and d2 arbitrarily small from Eqs. (8.40), (8.41), and (8.42), we obtain the lower bound for Prfnt > zg. j Lower and upper bounds given by Theorem 8.4.2 have the same exponent 2 1 H C 1 m , which depends only on the Hurst parameter H, server rate C expressed in units of single source rate, and average load of input traf c m. If C 1 m < 1=2 1 H , random variable nt will have stationary distribution with in nite mean Ent I, while for large values of C m the tail of the nt distribution will decrease suf ciently quickly. The variance of the input process Y does not appear in bounds; meanwhile, for exactly second-order self-similar processes, parameters c0 and l will be de ned by the mean and variance of the process Y . The best logarithmic bounds, obtained previously, for the probability Prfnt > zg are presented in the papers by Duf eld [3] and Liu et al. [10] (Pareto case). In our notation, exponents of these bounds are b C 1 m for the lower bound and min b; 1 b C m for the upper bound. As we can see, Theorem 8.4.2 corresponds to the previous results. Moreover, from Theorem 8.4.2 it follows that the lower bound obtained in Liu et al. [10] is indeed logarithmically exact.

In general, incremental backups are limited to filesystems, although some backup vendors do have technology that will permit the incremental backing up of databases. Specifically, to do an incremental backup of a filesystem, the blocks that have changed must be backed up. Once they are backed up, pointers and indices must be maintained so that the blocks can be put back into the database upon restore. Some solutions require a complete scan of the database for changed blocks. At least one solution (VERITAS NetBackup with the VERITAS File System, only available on Unix) keeps track of the blocks that have changed and does not need to do a full database scan in order to perform an incremental backup. As with all incremental backups, in order to perform a full restore, the tapes from the full and all of the incrementals (or only the most recent cumulative incremental tape) are required.

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