Indexing of Spatiotemporal Trajectories for Efficient Distance Threshold Similarity Searches on the GPU

Michael Gowanlock, Henri Casanova

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

14 Scopus citations

Abstract

Applications in many domains search moving object trajectory databases. The distance threshold search finds all trajectories within a given distance of a query trajectory. We develop three GPU distance threshold search implementations that use indexing techniques significantly different from those used in CPU implementations. We determine experimentally under which conditions each approach performs well using one real-world astrophysics dataset and two synthetic datasets. Overall, we find that the GPU is an attractive technology for a broad range of relevant trajectory database scenarios.

Original languageEnglish (US)
Title of host publicationProceedings - 2015 IEEE 29th International Parallel and Distributed Processing Symposium, IPDPS 2015
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages387-396
Number of pages10
ISBN (Electronic)9781479986484
DOIs
StatePublished - Jul 17 2015
Externally publishedYes
Event29th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2015 - Hyderabad, India
Duration: May 25 2015May 29 2015

Publication series

NameProceedings - 2015 IEEE 29th International Parallel and Distributed Processing Symposium, IPDPS 2015

Conference

Conference29th IEEE International Parallel and Distributed Processing Symposium, IPDPS 2015
Country/TerritoryIndia
CityHyderabad
Period5/25/155/29/15

Keywords

  • Distance threshold similarity search
  • GPGPU
  • moving object databases
  • query optimization

ASJC Scopus subject areas

  • Computer Networks and Communications

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