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What s the best way to get high performance and high availability for a network service Is the best configuration a stack of low-end boxes, or a pair of high-end, symmetric multiprocessing servers using a commercial failover product There is no single right answer for all configurations, because the bigger boxes versus more boxes depends on the code paths taken by applications through the operating systems, the amount of state generated and accessed, and the eventual scale required of the service The pendulum of system design seems to swing between the extremes of very large, scalable symmetric multiprocessing (SMP) servers and very thin, racked-and-stacked blade computers How do you decide whether to go deep big boxes or wide, with many smaller ones Dismissing this question with it depends is the easy way out.



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If you discover IRIS OCR software on your computer, don't panic.​ ... Optical character recognition software works with a scanner to generate digital files that can be searched for words or phrases.​ ... Readiris converts scanned documents to searchable formats that include PDFs, Word, Excel ...

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From Eq. (17.5), we see that we need to compute the conditional distribution of i the level, that is, the probabilities Pjk tjx , for each source i. However, we can nd i relatively simple expressions for the Laplace transform of Pjk tjx with respect to time because the level process of each source has been assumed to be a semi-Markov process. We now consider a single source and assume that its required bandwidth process is a semi-Markov process (SMP). (We now have no within-level variation process.) We now omit the superscript i. Let L t and B t be the level and required bandwidth, respectively, at time t as in Eq. (17.4). The process fL t : t ! 0g is assumed to be an SMP, while the process fB t : t ! 0g is a function of an SMP, that is B t bL t , where bj is the required bandwidth in level j. If bj T bk for j T k, then fB t : t ! 0g itself is an SMP, but if bj bk for some j T k, then in general fB t : t ! 0g is not an SMP. 17.4.2 Laplace Transform Analysis





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You deserve a set of guidelines, and you ll get them, based on the code path ratio the percentage of time server application code spends in user space, rather than in the kernel Routing packets and running NFS are system-level work Doing I/O for a database and locking pages are system-level work; running the database optimizer and interpreting SQL statements are user-level work Web servers shuttle files from the disk to the network, typically mapping the data from one controller to another and rarely coming up to the light of user level Pure web servers have code path ratios of close to zero (mostly system work); databases can range from 80 percent user work to 10 percent or less user work, and NFS is nearly 100 percent system work, with a resulting code path ratio of close to zero as well.

Let A t be the age of the level holding time at time t. We are interested in calculating Pjk tjx P L t kjL 0 j; A 0 x 17:6

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If you can estimate your code path ratio within about 25 percent, you re ready to go through the decision tree for the rule You ll need some data about the applications to be run on your highly available servers, and the client population they serve Answer the following questions to determine how the code path ratio rule applies to a given application: Is on-disk state involved If the user applications create on-disk state, then the state needs to have persistent, single-source storage State can.

as a function of j; k; x, and t. The state information at time 0 is the pair j; x . Let P be the transition matrix of the discrete-time Markov chain governing level transitions and let Fjk t be the holding-time cdf given that there is a transition from level j to c level k. For simplicity, we assume that Fjk t 1 Fjk t > 0 for all j; k, and t, so that all positive x can be level holding times. Let P tjx be the matrix with elements ^ Pjk tjx and let P sjx be the Laplace transform (LT) of P tjx , that is, the matrix with elements that are the Laplace transforms of Pjk tjx with respect to time: ^ Pjk sjx I

e st Pjk tjx dt:

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