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Abstract
We present a simple lazy buffering technique for performing bulk operations on multidimensional spatial indexes (data structures), and show that it is efficient in theory as well as in practice. We present the technique in terms of the so-called R-tree and its variants, as they have emerged as practically efficient indexing methods for spatial data.
Supported in part by the U.S. Army Research Office through MURI grant DAAH04-96-1-0013 and by the National Science Foundation through ESS grant EIA-9870734.
Part of this work was done while a visiting scholar at Duke University.
Supported in part by the U.S. Army Research Office through MURI grant DAAH04-96-1-0013 and by the National Science Foundation through grants CCR-9522047 and EIA-9870734.
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Author information
Authors and Affiliations
Center for Geometric Computing, Department of Computer Science, Duke University, Durham, NC, 27708, USA
Lars Arge & Jeffrey S. Vitter
Institut für Informatik, Westfälische Wilhelms-Universität, 48149, Münster, Germany
Klaus H. Hinrichs & Jan Vahrenhold
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Editor information
Editors and Affiliations
Department of Computer Science, John Hopkins University, Baltimore, MD, 21218, USA
Michael T. Goodrich
Department of Mathematics and Computer Science, Amherst University, Amherst, MA, 01002, USA
Catherine C. McGeoch
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Arge, L., Hinrichs, K.H., Vahrenhold, J., Vitter, J.S. (1999). Efficient Bulk Operations on Dynamic R-trees. In: Goodrich, M.T., McGeoch, C.C. (eds) Algorithm Engineering and Experimentation. ALENEX 1999. Lecture Notes in Computer Science, vol 1619. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-48518-X_20
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