Abstract
In this paper, a top-down data placement methodology for a large intertive muliimedia information system (MMIS) on a single spindle multi-disk environment such as a Jukebox is presented. The objective of this work is to minimize aveiage disk seek time as well as the number of platter switehes fcw Jukebox. A large data placement problem can be divided into a number of small data placement problems by weighted graph decomposition. The Kernighan-Lin partitioning algorithm is recursively applied for this jiirpoac. Once the graph is fully partitioned, the objects in the same subgraph are assigned to the same disk. The data placement within a disk is divided into two stages, global data placement and detailed data placement. The expected access patterns of global data placement are modeled as a time-homogeneous ergodic Markov Chain, from which the stationary probability for each node of the browsing graph can be found. Based on these probabilities, we define an expected access cost Then, the problem of global data placement is posed as an optimization problem, and various clustering and storage layout algxithms are proposed.
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