Tree Embeddings for Hop-Constrained Network Design

TL;DR

This paper introduces a novel method to approximate hop-constrained distances in graphs using distributions over partial tree metrics, enabling efficient solutions for complex network design problems with hop constraints.

Contribution

It develops a new approach to approximate hop-constrained distances via partial tree metrics, leading to the first poly-logarithmic bicriteria approximations for several hop-constrained network design problems.

Findings

Provides a probabilistic tree embedding technique for hop-constrained distances.

Achieves poly-logarithmic bicriteria approximation algorithms for multiple network design problems.

Extends solutions to online and oblivious variants of these problems.

Abstract

Network design problems aim to compute low-cost structures such as routes, trees and subgraphs. Often, it is natural and desirable to require that these structures have small hop length or hop diameter. Unfortunately, optimization problems with hop constraints are much harder and less well understood than their hop-unconstrained counterparts. A significant algorithmic barrier in this setting is the fact that hop-constrained distances in graphs are very far from being a metric. We show that, nonetheless, hop-constrained distances can be approximated by distributions over "partial tree metrics." We build this result into a powerful and versatile algorithmic tool which, similarly to classic probabilistic tree embeddings, reduces hop-constrained problems in general graphs to hop-unconstrained problems on trees. We then use this tool to give the first poly-logarithmic bicriteria approximations for the hop-constrained variants of many classic network design problems. These include Steiner forest, group Steiner tree, group Steiner forest, buy-at-bulk network design as well as online and oblivious versions of many of these problems.