Optimal message-passing with noisy beeps.

Abstract

Beeping models are models for networks of weak devices, such as sensor networks or biological networks. In these networks, nodes are allowed to communicate only via emitting beeps: unary pulses of energy. Listening nodes have only the capability of carrier sensing: they can only distinguish between the presence or absence of a beep, but receive no other information. The noisy beeping model further assumes listening nodes may be disrupted by random noise. Despite this extremely restrictive communication model, it transpires that complex distributed tasks can still be performed by such networks. In this paper we provide an optimal procedure for simulating general message passing in the beeping and noisy beeping models. We show that a round of Broadcast CONGEST can be simulated in $O(\Delta logn)$ rounds of the noisy (or noiseless) beeping model, and a round of CONGEST can be simulated in $O({\Delta }^{2}logn)$ rounds (where $\Delta$ is the maximum degree of the network). We also prove lower bounds demonstrating that no simulation can use asymptotically fewer rounds. This allows a host of graph algorithms to be efficiently implemented in beeping models. We present several example applications, including an $O(logn)$ -round Broadcast CONGEST algorithm for maximal matching, which, when simulated using our method, immediately implies a near-optimal $O\left(\Delta {log}^{2}n\right)$ -round maximal matching algorithm in the noisy beeping model. A preliminary version of this paper appeared in the proceedings of the 2023 ACM Symposium on Principles of Distributed Computing (PODC) [14].