The architectural concept of a memory hierarchy has been  immensely successful, making possible today's spectacular pace of  technology evolution in both the volume of data and the speed of data  access. Its success is difficult to understand, however, when examined  within the traditional ''memoryless'' framework of performance analysis.  The `memoryless' framework cannot properly reflect a memory  hierarchy's ability to take advantage of patterns of data use that are  transient. The Fractal Structure of Data Reference: Applications to  the Memory Hierarchy both introduces, and justifies  empirically, an alternative modeling framework in which arrivals are  driven by a statistically self-similar underlying process, and are  transient in nature. The substance of this book comes from the ability  of the model to impose a mathematically tractable structure on  important problems involving the operation and performance of a memory  hierarchy. It describes events as they play out at a wide range of  time scales, from the operation of file buffers and storage control  cache, to a statistical view of entire disk storage applications.  Striking insights are obtained about how memory hierarchies work, and  how to exploit them to best advantage. The emphasis is on the  practical application of such results.   The Fractal Structure of Data Reference: Applications to the  Memory Hierarchy will be of interest to professionals working  in the area of applied computer performance and capacity planning,  particularly those with a focus on disk storage. The book is also an  excellent reference for those interested in database and data  structure research.

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