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THE FRACTAL STRUCTURE OF DATA REFERENCE- P23

THE FRACTAL STRUCTURE OF DATA REFERENCE- P23:For purposes of understanding its performance, a computer system is traditionally viewed as a processor coupled to one or more disk storage devices, and driven by externally generated requests (typically called transactions). Over the past several decades, very powerful techniques have become available to the performance analyst attempting to understand, at a high level, the operational behavior of such systems. | Transient and Persistent Data Access 99 in defining which ones are active the more storage they will require. Thus this case would be represented by a straight line sloping upward 3. A series of transient files which are created at random times referenced at the time that they are created not referenced afterward and scratched after some waiting period. For files with this behavior being created and scratched at a constant rate the average amount of allocated storage Salloc would not change with time. Since Figure 7.14 represents the average amount of allocated storage that is active within a specific window the curves presented by the figure for a case of this type would always lie below Sauoc. Thus at its right extreme the curve would have a horizontal asymptote equal to Sauoc. At its left extreme for window sizes shorter than the shortest waitingperiod the curve would begin as a straight line sloping upward. Joining the two extremes the curve would have a knee. The curve would bend most sharply at the region of window sizes just past the typical waiting period . The thought experiment just presented suggests that to discover transient data that are being created but not scratched we can look in Figure 7.14 for a straight line sloping up. This appears to exist in the part of the curves past about 10-15 days suggesting that most files that behave as in 3 will be scratched by the time they are one week old. Thus a retention period of one week on primary storage again appears to be reasonable this time relative to the goal of allowing data to be scratched before bothering to migrate it. It should be emphasized that the cases 1-3 present a thought experiment not a full description of a realistic environment. Any real life environment would include a much richer variety of cases than the simple set of three just considered. Since the curves of Figure 7.14 deliberately ignore the impact of storage management they help to clarify its importance. Without storage .