# Faster and Smaller Two-Level Index for Network-based Trajectories

## TL;DR

This paper introduces a compact data structure for the bottom level of two-level network trajectory indexes, significantly improving speed and size efficiency over existing methods.

## Contribution

It presents a novel, specialized data structure for the interval-intersection problem in network trajectory indexing, outperforming non-specialized spatial indexes.

## Key findings

- Faster query processing times
- Reduced index size
- Improved overall efficiency

## Abstract

Two-level indexes have been widely used to handle trajectories of moving objects that are constrained to a network. The top-level of these indexes handles the spatial dimension, whereas the bottom level handles the temporal dimension. The latter turns out to be an instance of the interval-intersection problem, but it has been tackled by non-specialized spatial indexes. In this work, we propose the use of a compact data structure on the bottom level of these indexes. Our experimental evaluation shows that our approach is both faster and smaller than existing solutions.