Limit Laws for Consensus Protocols on the Complete Graph
Julian Becker, Konstantinos Panagiotou

TL;DR
This paper analyzes the distribution of consensus times in distributed protocols on complete graphs, considering adversarial noise and a broad class of update functions, revealing complex asymptotic periodic behaviors.
Contribution
It characterizes the limiting distributions of consensus times for a wide class of protocols, including the $k$-majority, under adversarial conditions, with explicit asymptotic formulas.
Findings
Consensus time $R_n$ centers around $rac{1}{2} ext{log}_ ext{gamma} n + ext{log}_m ext{ln} n
The distribution of $R_n - ext{center}$ does not converge and is asymptotically periodic
Explicit asymptotic constants are derived for the $k$-majority protocol
Abstract
We study a distributed consensus problem on a complete communication network of vertices, each holding one of two opinions. The vertices communicate in rounds, possibly in the presence of adversarial noise, and exchange information until they all agree on a single opinion. We consider a general class of protocols, where the vertices randomly sample neighbors and update their own opinion according to an update function depending on the sampled opinions. A prominent example is the -maj protocol, where every vertex adopts the majority opinion of randomly sampled neighbors. We consider the runtime that is the number of rounds until all vertices agree on the same opinion, which we call the dominating opinion . In our main result we describe the limiting distributions of these two key quantities for a large class of update functions , for arbitrary initial…
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