English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Plus monthly

Global: Zendy Tools annual

Global: Zendy Tools monthly

Global: Zendy Free Plan

Applications in many domains require processing moving object trajectories.In this work, we focus on a trajectory similarity search that finds alltrajectories within a given distance of a query trajectory over a timeinterval, which we call the distance threshold similarity search. We developthree indexing strategies with spatial, temporal and spatiotemporal selectivityfor the GPU that differ significantly from indexes suitable for the CPU, andshow the conditions under which each index achieves good performance.Furthermore, we show that the GPU implementations outperform multithreaded CPUimplementations in a range of experimental scenarios, making the GPU anattractive technology for processing moving object trajectories. We test ourimplementations on two synthetic and one real-world dataset of a galaxy merger.

Technical Report: Towards Efficient Indexing of Spatiotemporal Trajectories on the GPU for Distance Threshold Similarity Searches