English

Distance Computations in the Hybrid Network Model via Oracle Simulations

Distributed, Parallel, and Cluster Computing 2021-01-19 v2

Abstract

The Hybrid network model was introduced in [Augustine et al., SODA '20] for laying down a theoretical foundation for networks which combine two possible modes of communication: One mode allows high-bandwidth communication with neighboring nodes, and the other allows low-bandwidth communication over few long-range connections at a time. This fundamentally abstracts networks such as hybrid data centers, and class-based software-defined networks. Our technical contribution is a \emph{density-aware} approach that allows us to simulate a set of \emph{oracles} for an overlay skeleton graph over a Hybrid network. As applications of our oracle simulations, with additional machinery that we provide, we derive fast algorithms for fundamental distance-related tasks. One of our core contributions is an algorithm in the Hybrid model for computing \emph{exact} weighted shortest paths from O~(n1/3)\tilde O(n^{1/3}) sources which completes in O~(n1/3)\tilde O(n^{1/3}) rounds w.h.p. This improves, in both the runtime and the number of sources, upon the algorithm of [Kuhn and Schneider, PODC '20], which computes shortest paths from a single source in O~(n2/5)\tilde O(n^{2/5}) rounds w.h.p. We additionally show a 2-approximation for weighted diameter and a (1+ϵ)(1+\epsilon)-approximation for unweighted diameter, both in O~(n1/3)\tilde O(n^{1/3}) rounds w.h.p., which is comparable to the Ω~(n1/3)\tilde \Omega(n^{1/3}) lower bound of [Kuhn and Schneider, PODC '20] for a (2ϵ)(2-\epsilon)-approximation for weighted diameter and an exact unweighted diameter. We also provide fast distance \emph{approximations} from multiple sources and fast approximations for eccentricities.

Keywords

Cite

@article{arxiv.2010.13831,
  title  = {Distance Computations in the Hybrid Network Model via Oracle Simulations},
  author = {Keren Censor-Hillel and Dean Leitersdorf and Volodymyr Polosukhin},
  journal= {arXiv preprint arXiv:2010.13831},
  year   = {2021}
}

Comments

To appear in STACS 2021

R2 v1 2026-06-23T19:39:53.314Z