English

A new method to index and store spatio-temporal data

Data Structures and Algorithms 2016-11-18 v1

Abstract

We propose a data structure that stores, in a compressed way, object trajectories, which at the same time, allow to efficiently response queries without the need to decompress the data. We use a data structure, called k2k^{2}-tree, to store the full position of all objects at regular time intervals. For storing the positions of objects between two time instants represented with k2k^{2}-trees, we only encode the relative movements. In order to save space, those relative moments are encoded with only one integer, instead of two (x,y)-coordinates. Moreover, the resulting integers are further compressed with a technique that allows us to manipulate those movements directly in compressed form. In this paper, we show an experimental evaluation of this structure, which shows important savings in space and good response times.

Keywords

Cite

@article{arxiv.1611.05247,
  title  = {A new method to index and store spatio-temporal data},
  author = {Guillermo de Bernardo and Ramón Casares and Adrián Gómez-Brandón and José R. Paramá},
  journal= {arXiv preprint arXiv:1611.05247},
  year   = {2016}
}

Comments

This research has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sk{\l}odowska-Curie Actions H2020-MSCA-RISE-2015 BIRDS GA No. 690941

R2 v1 2026-06-22T16:54:13.104Z