Relative compression of trajectories

TL;DR

This paper introduces RCT, a novel data structure for efficiently compressing and querying object trajectories using relative compression techniques, aiming to surpass existing methods in compression ratio and query performance.

Contribution

The paper proposes RCT, a new compact data structure based on Relative Lempel-Ziv compression for trajectories, improving compression and query efficiency over prior approaches.

Findings

RCT achieves better compression ratios than previous methods.

RCT enables efficient trajectory and spatio-temporal queries.

The approach demonstrates improved time performance in trajectory data handling.

Abstract

We present RCT, a new compact data structure to represent trajectories of objects. It is based on a relative compression technique called Relative Lempel-Ziv (RLZ), which compresses sequences by applying an LZ77 encoding with respect to an artificial reference. Combined with $O(z)$-sized data structures on the sequence of phrases that allows to solve trajectory and spatio-temporal queries efficiently. We plan that RCT improves in compression and time performance the previous compressed representations in the state of the art.