Fast Hybrid Network Algorithms for Shortest Paths in Sparse Graphs

TL;DR

This paper introduces fast algorithms for shortest paths in hybrid networks, leveraging local and global communication modes, achieving significant speedups in sparse graph classes like cactus graphs and low-arboricity graphs.

Contribution

It presents the first efficient algorithms for shortest paths in hybrid networks on specific sparse graph classes, improving over previous general algorithms.

Findings

Exact $O( ext{log} n)$ algorithms for cactus graphs.

3-approximation algorithms for sparse graphs with $n + O(n^{1/3})$ edges.

Algorithms outperform existing methods exponentially in certain graph classes.

Abstract

We consider the problem of computing shortest paths in hybrid networks, in which nodes can make use of different communication modes. For example, mobile phones may use ad-hoc connections via Bluetooth or Wi-Fi in addition to the cellular network to solve tasks more efficiently. Like in this case, the different communication modes may differ considerably in range, bandwidth, and flexibility. We build upon the model of Augustine et al. [SODA '20], which captures these differences by a local and a global mode. Specifically, the local edges model a fixed communication network in which $O(1)$ messages of size $O(\log n)$ can be sent over every edge in each synchronous round. The global edges form a clique, but nodes are only allowed to send and receive a total of at most $O(\log n)$ messages over global edges, which restricts the nodes to use these edges only very sparsely. We demonstrate the power of hybrid networks by presenting algorithms to compute Single-Source Shortest Paths and the diameter very efficiently in sparse graphs. Specifically, we present exact $O(\log n)$ time algorithms for cactus graphs (i.e., graphs in which each edge is contained in at most one cycle), and $3$-approximations for graphs that have at most $n + O(n^{1/3})$ edges and arboricity $O(\log n)$. For these graph classes, our algorithms provide exponentially faster solutions than the best known algorithms for general graphs in this model. Beyond shortest paths, we also provide a variety of useful tools and techniques for hybrid networks, which may be of independent interest.