Shortest Paths in a Hybrid Network Model

TL;DR

This paper explores how combining local and global communication modes in hybrid networks affects the complexity of shortest path problems, providing new algorithms with improved time bounds for exact and approximate solutions.

Contribution

It introduces a hybrid communication model and presents novel algorithms for shortest path problems with improved time complexities.

Findings

Exact APSP in  O(n^{2/3}) time

Approximate APSP in  heta(\u221a n) time

Exact SSSP in  O(\u221a ext{SPD}) time

Abstract

We introduce a communication model for hybrid networks, where nodes have access to two different communication modes: a local mode where communication is only possible between specific pairs of nodes, and a global mode where communication between any pair of nodes is possible. This can be motivated, for instance, by wireless networks in which we combine direct device-to-device communication (e.g., using WiFi) with communication via a shared infrastructure (like base stations, the cellular network, or satellites). Typically, communication over short-range connections is cheaper and can be done at a much higher rate. Hence, we are focusing here on the LOCAL model (in which the nodes can exchange an unbounded amount of information in each round) for the local connections while for the global communication we assume the so-called node-capacitated clique model, where in each round every node can exchange only $O(\log n)$-bit messages with just $O(\log n)$ other nodes. In order to explore the power of combining local and global communication, we study the impact of hybrid communication on the complexity of computing shortest paths in the graph given by the local connections. Specifically, for the all-pairs shortest paths problem (APSP), we show that an exact solution can be computed in time $\tilde O\big(n^{2/3}\big)$ and that approximate solutions can be computed in time $\tilde \Theta\big(\!\sqrt{n}\big)$. For the single-source shortest paths problem (SSSP), we show that an exact solution can be computed in time $\tilde O\big(\!\sqrt{\mathsf{SPD}}\big)$, where $\mathsf{SPD}$ denotes the shortest path diameter. We further show that a $\big(1\!+\!o(1)\big)$-approximate solution can be computed in time $\tilde O\big(n^{1/3}\big)$. Additionally, we show that for every constant $\varepsilon>0$, it is possible to compute an $O(1)$-approximate solution in time $\tilde O(n^\varepsilon)$.