A well-separated pair decomposition for low density graphs

TL;DR

This paper introduces a well-separated pair decomposition and an approximate distance oracle for low density graphs, enhancing their utility for modeling road networks and expanding the algorithmic toolkit for this graph class.

Contribution

The paper develops two fundamental tools—well-separated pair decomposition and approximate distance oracle—for low density graphs, facilitating their application in road network modeling.

Findings

Tools improve analysis of low density graphs

Enhances modeling of road networks

Supports development of efficient heuristics

Abstract

Low density graphs are considered to be a realistic graph class for modelling road networks. It has advantages over other popular graph classes for road networks, such as planar graphs, bounded highway dimension graphs, and spanners. We believe that low density graphs have the potential to be a useful graph class for road networks, but until now, its usefulness is limited by a lack of available tools. In this paper, we develop two fundamental tools for low density graphs, that is, a well-separated pair decomposition and an approximate distance oracle. We believe that by expanding the algorithmic toolbox for low density graphs, we can help provide a useful and realistic graph class for road networks, which in turn, may help explain the many efficient and practical heuristics available for road networks.