An investigation of multi-level k-ranges

dc.contributor.authorFalconer, Sean, M.
dc.contributor.authorNickerson, Bradford, G.
dc.date.accessioned2023-03-01T18:29:55Z
dc.date.available2023-03-01T18:29:55Z
dc.date.issued2004
dc.description.abstractMulti-level k-ranges are an efficient theoretical data structure for range searching introduced by J. L. Bentley and H. A. Maurer. Bentley and Maurer showed that a 1-level k-range offers O(k log N + A) query time, where k is the number of dimensions, N is the number of data points and A is the number of points matching the query at the expense of O(N[superscript 2k−1]) storage. They also introduced the multi-level k-range, which offers slightly slower query time but with O(N[superscript 1+e]) storage for any fixed values of k and e > 0. In this paper, we investigate an implementation of the multi-level k-range data structure. The l-level k-range is compared to naive and R*tree search over N randomly generated k-d points. We show that the R*tree search is significantly faster and that even naive search is faster for most test cases. Results indicate that multi-level k-ranges are not competitive due to their (previously unreported) complexity. Our results indicate that l-level k-ranges require Q(N, k, l) = O((2l)[superscript (k−1)](log N + A)) time for range search. We show that S(N, k, l) = O(N[superscript 1+2(k−1)/l]) and when N does not equal a[superscript l] where a and l are positive integers, S(N, k) = O(N[superscript 1+2(k−1)]/ log[subscript 2] N).
dc.description.copyrightCopyright @ Sean M. Falconer and Bradford G. Nickerson, 2004.
dc.identifier.urihttps://unbscholar.lib.unb.ca/handle/1882/14959
dc.rightshttp://purl.org/coar/access_right/c_abf2
dc.subject.disciplineComputer Science
dc.titleAn investigation of multi-level k-ranges
dc.typetechnical report

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