Distributed Consensus in Wireless Networks with Probabilistic Broadcast Scheduling

TL;DR

This paper proposes a probabilistic broadcast scheduling method for distributed average consensus in wireless networks, aiming to reduce transmissions while maintaining accuracy, and introduces bias correction techniques for improved consensus.

Contribution

It introduces a novel probabilistic scheduling approach for wireless consensus, along with bias correction and heuristic methods for probability assignment.

Findings

Reduced number of transmissions in consensus rounds

Effective bias correction method for consensus accuracy

Comparable or improved convergence with probabilistic scheduling

Abstract

We consider distributed average consensus in a wireless network with partial communication to reduce the number of transmissions in every iteration/round. Considering the broadcast nature of wireless channels, we propose a probabilistic approach that schedules a subset of nodes for broadcasting information to their neighbors in every round. We compare several heuristic methods for assigning the node broadcast probabilities under a fixed number of transmissions per round. Furthermore, we introduce a pre-compensation method to correct the bias between the consensus value and the average of the initial values, and suggest possible extensions for our design. Our results are particularly relevant for developing communication-efficient consensus protocols in a wireless environment with limited frequency/time resources.