GraCT: A Grammar based Compressed representation of Trajectories

TL;DR

GraCT is a novel compressed data structure that efficiently stores and queries moving object trajectories by combining snapshot-based absolute positions with compressed relative movement logs.

Contribution

It introduces GraCT, integrating $k^2$-trees and Re-Pair compression to improve space and time efficiency in trajectory data storage and querying.

Findings

Significant space savings over baseline methods.

Faster query processing times.

Effective compression of movement logs.

Abstract

We present a compressed data structure to store free trajectories of moving objects (ships over the sea, for example) allowing spatio-temporal queries. Our method, GraCT, uses a $k^2$-tree to store the absolute positions of all objects at regular time intervals (snapshots), whereas the positions between snapshots are represented as logs of relative movements compressed with Re-Pair. Our experimental evaluation shows important savings in space and time with respect to a fair baseline.