On the optimality of clustering properties of space filling curves

Pan Xu, Srikanta Tirthapura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

Space filling curves have for long been used in the design of data structures for multidimensional data. A fundamental quality metric of a space filling curve is its "clustering number" with respect to a class of queries, which is the average number of contiguous segments on the space filling curve that a query region can be partitioned into. We present a characterization of the clustering number of a general class of space filling curves, as well as the first non-trivial lower bounds on the clustering number for any space filling curve. Our results also answer an open problem that was posed by Jagadish in 1997.

Original languageEnglish (US)
Title of host publicationPODS '12 - Proceedings of the 31st Symposium on Principles of Database Systems
Pages215-224
Number of pages10
DOIs
StatePublished - 2012
Externally publishedYes
Event31st ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS '12 - Scottsdale, AZ, United States
Duration: May 21 2012May 23 2012

Publication series

NameProceedings of the ACM SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems

Conference

Conference31st ACM SIGMOD-SIGACT-SIGART Symposium on Principles of Database Systems, PODS '12
Country/TerritoryUnited States
CityScottsdale, AZ
Period5/21/125/23/12

All Science Journal Classification (ASJC) codes

  • Software
  • Information Systems
  • Hardware and Architecture

Keywords

  • clustering
  • hilbert curve
  • lower bound
  • space filling curve

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