MIS on the fly

TL;DR

This paper introduces a practical, randomized distributed MIS algorithm inspired by biological systems, achieving near-optimal round complexity with minimal communication and relaxed assumptions, applicable to asynchronous and unknown network environments.

Contribution

It presents a new distributed MIS algorithm that operates efficiently with minimal communication, asynchronous wake-up, and no prior network knowledge, extending previous models and establishing a tight lower bound.

Findings

O(log^2 n) rounds with collision detection

O(log^3 n) rounds without collision detection

Proven optimality with a lower bound of Ω(log^2 n)

Abstract

Humans are very good at optimizing solutions for specific problems. Biological processes, on the other hand, have evolved to handle multiple constrained distributed environments and so they are robust and adaptable. Inspired by observations made in a biological system we have recently presented a simple new randomized distributed MIS algorithm \cite{ZScience}. Here we extend these results by removing a number of strong assumptions that we made, making the algorithms more practical. Specifically we present an $O(\log^2 n)$ rounds synchronous randomized MIS algorithm which uses only 1 bit unary messages (a beeping signal with collision detection), allows for asynchronous wake up, does not assume any knowledge of the network topology, and assumes only a loose bound on the network size. We also present an extension with no collision detection in which the round complexity increases to $(\log^3 n)$. Finally, we show that our algorithm is optimal under some restriction, by presenting a tight lower bound of $\Omega(\log^2 n)$ on the number of rounds required to construct a MIS for a restricted model.