Browsing by Author "Schaffer, Alejandro A."

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    Dynamic multiple pattern matching
    (1994) Idury, Ramana Murthy; Schaffer, Alejandro A.
    Pattern matching algorithms are among the most important and practical contribution of theoretical computer science. Pattern matching is used in a wide variety of applications such as text editing, information retrieval, DNA sequencing, and computer vision. Several combinatorial problems arise in pattern matching such as matching in the presence of local errors, scaling, rotation, compression, and multiple patterns. A common feature shared by many solutions to these problems is the notion of preprocessing the patterns and/or texts prior to the actual matching. We study the problem of pattern matching with multiple patterns. The set of patterns is called a dictionary. Furthermore, the dictionary can be dynamic in the sense that it can change over time by insertion or deletion of individual patterns. We need to preprocess the dictionary so as to provide efficient searching as well as efficient updates. We first present a solution to the one dimensional version of the problem where the patterns are strings. A salient feature of our solution is a DFA-based searching mechanism similar to the Knuth-Morris-Pratt algorithm. We then use this solution to solve the two dimensional version of the problem where the patterns are restricted to have square shapes. Finally we solve the general case, where the patterns can have any rectangular shape, by reducing this problem to a range searching problem in computational geometry.
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    Markov analysis of multiple-disk prefetching strategies for external merging
    (Elsevier Science Publishers Ltd. Essex, UK, 1994-06-06) Sadananda Pai, Vinay; Schaffer, Alejandro A.; Varman, Peter J.
    Multiple-disk organizations can be used to improve the I/O performance of problems like external merging. Concurrency can be introduced by overlapping I/O requests at different disks and by prefetching additional blocks on each I/O operation. To support this prefetching, a memory cache is required. Markov models for two prefetching strategies are developed and analyzed. Closed-form expressions for the average parallelism obtainable for a given cache size and number of disks are derived for both prefetching strategies. These analytic results are confirmed by simulation.