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in the number of tape drives and libraries that are required for backups, saving the enterprise considerable amounts of capital. A new technique has been developed specifically for SANs that can speed up backups even more. This technique, third-party copy, uses specialized hardware called data movers to copy data from disk storage to tape, without all of the network overhead that standard backup methods bring along. The result is backups that run even faster, and with less of an impact on hosting servers. Data movers are available from companies like Chaparral Network Storage and Crossroads Systems. Generally, SANs are faster than LANs, and so backups that send their data across the LAN will be faster and more efficient that those that use a LAN.



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where the En are independent and identically distributed normal random variables with mean zero. For the rest of the intrascene frames, the autocorrelation function and the distribution are important. Figure 13 in Verbiest and Pannoo [30] shows an autocorrelation function of a TV scene; it does not decline geometrically to zero as the video conference scenes do. We obtain similar functions when all of the intrascene frames (excluding the rst two frames of each scene) are treated as a single time series. The left side of Fig. 12.10 shows this function for im and Isaura 1. This method of estimating the autocorrelation function ignores scene boundaries. For example, the last frame of a scene and the rst (counted) frame of the subsequent scene contribute to the lag one term in the autocorrelation function. For lm, this causes the autocorrelation function to have periodic pulses, as shown in Fig. 12.10(c). These pulses are not present in the autocorrelation functions of the rst six scenes and are just an artifact of the aggregation across scenes. A more re ned estimate is obtained by dividing the data into scenes, calculating the empirical autocorrelation function for each scene, and then averaging over the scenes. To be





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Like so many new technologies, SANs come with their own terminology and hardware menagerie. Although we cannot teach you all there is to know about SANs in this brief section, we will end our discussion of SANs with a quick look at the important hardware components that make up SANs and that you ll need to be familiar with if you are thinking about implementing one. Three types of devices connect to a SAN: initiators, targets, and interconnects. Initiators put requests onto the SAN. Those requests travel through interconnecting devices until they arrive at a target. Targets service the request and send the response across the same interconnecting devices in the opposite direction, until they arrive back at the initiator. Host bus adapter. The host bus adapter (or HBA) is an adapter board that sits in a host computer and initiates all communication between the host and the SAN. If a device requests information from storage on a SAN, then that device requires an HBA. The device could even be a computer system, or an intelligent tape drive that does its backups directly from the SAN-based storage, or a data mover. Switches. The backbone of the SAN architecture, they provide a highspeed interconnect between different devices on the SAN, and they route blocks of data from one device to another. Fabric. The virtual infrastructure that is formed by all of the interconnected switches on a SAN. Router. A router connects two different protocols, such as Fibre Channel to Ethernet, in a many-to-one or many-to-many configuration. Bridge. A bridge is a router that only supports one-to-one connections. In the SAN world, the terms router and bridge are often used interchangeably.

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6 M Crovella and A Bestavros Self-similarity in World Wide Web traf c: evidence and possible causes Perf Eval Rev, 24:160 169, 1996; Proc ACM SIGMETRICS'96, Philadelphia, May 1996 7 D R Cox and V Isham Point Processes, Chapman and Hall, New York, 1980 8 D R Cox Long-range dependence: a review In H A David and H T David, eds, Statistics: An Appraisal, pp 55 74 The Iowa State University Press, Ames, 1984 9 A Dembo and O Zeitouni Large Deviation Techniques and Applications Jones and Bartlett, Boston, 1993 10 N G Duf eld and N O'Connell Large deviations and over ow probabilities for the general single server queue, with applications Proc Cambridge Philos Soc, 118:363 374, 1995 11 N G Duf eld On the relevance of long-tailed durations for the statistical multiplexing of large aggregations.

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