An Almost Singularly Optimal Asynchronous Distributed MST Algorithm
Fabien Dufoulon, Shay Kutten, William K. Moses Jr., Gopal Pandurangan,, and David Peleg

TL;DR
This paper introduces a randomized asynchronous distributed MST algorithm that is nearly optimal in both time and message complexity, solving a longstanding open problem in distributed computing.
Contribution
It presents the first asynchronous MST algorithm with sublinear time and message complexity, nearly matching the optimal bounds in asynchronous networks.
Findings
Achieves $ ilde{O}(D^{1+ extepsilon} + extsqrt{n})$ time complexity.
Uses $ ilde{O}(m)$ messages, nearly message optimal.
Constructs a low diameter spanning tree with near-optimal depth and complexity.
Abstract
A singularly (near) optimal distributed algorithm is one that is (near) optimal in \emph{two} criteria, namely, its time and message complexities. For \emph{synchronous} CONGEST networks, such algorithms are known for fundamental distributed computing problems such as leader election [Kutten et al., JACM 2015] and Minimum Spanning Tree (MST) construction [Pandurangan et al., STOC 2017, Elkin, PODC 2017]. However, it is open whether a singularly (near) optimal bound can be obtained for the MST construction problem in general \emph{asynchronous} CONGEST networks. We present a randomized distributed MST algorithm that, with high probability, computes an MST in \emph{asynchronous} CONGEST networks and takes time and messages, where is the number of nodes, the number of edges, is the diameter of the network, and $\epsilon…
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