Distributed Finite-Time Termination for Consensus Algorithm in Switching Topologies

In this article, we present a finite-time stopping criterion for consensus algorithms in networks with dynamic communication topology. Prior state of the art has established convergence to the consensus value; however, the asymptotic convergence of these algorithms poses a challenge in practical settings where the response from agents is required in finite time. To this end, we propose a maximum-minimum protocol that propagates the global maximum and minimum values of agent states (while running the consensus algorithm) in the network. This article focuses on establishing that the global maximum and minimum values are strictly monotonic even for a dynamic topology, and they can be used to distributively ascertain the closeness to convergence in finite time. We rigorously show that each node can have access to the global maximum and minimum by running the proposed maximum-minimum protocol to realize a finite-time stopping criterion for the otherwise asymptotic consensus algorithm. The practical utility of the algorithm is illustrated through experiments where each agent is instantiated by a NodeJS socket.io server.

Automated summary

This article presents a finite-time stopping criterion for consensus algorithms in networks with dynamic communication topology. It proposes a maximum-minimum protocol to propagate global maximum and minimum values of agent states, allowing for a distributive determination of convergence in finite time. Experimental results illustrate the practical utility of the algorithm.