Efficient Searching with Linear Constraints (Extended Abstract)
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@MISC{Agarwal_efficientsearching,
author = {Pankaj K. Agarwal and Lars Arge and Jeff Erickson and Paolo G. Franciosa and Jeffrey Scott Vitter},
title = {Efficient Searching with Linear Constraints (Extended Abstract)},
year = {}
}
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Abstract
) Pankaj K. Agarwal Lars Arge y Jeff Erickson z Paolo G. Franciosa x Jeffrey Scott Vitter -- Abstract We show how to preprocess a set S of points in R d to get an external memory data structure that efficiently supports linear-constraint queries. Each query is in the form of a linear constraint a \Delta x b; the data structure must report all the points of S that satisfy the query. Our goal is to minimize the number of disk blocks required to store the data structure and the number of disk accesses (I/Os) required to answer a query. For d = 2, we present the first near-linear size data structures that can answer linear-constraint queries using an optimal number of I/Os. We also present a linear-size data structure that can answer queries efficiently in the worst case. We combine these two approaches to obtain tradeoffs between space and query time. Finally, we show that some of our techniques extend to higher dimensions d. Center for Geometric Computing, Computer...
