Consensus-Based Distributed Computation of Link-Based Network Metrics

TL;DR

This paper introduces a distributed algorithm for computing link-based network metrics in networks, extending average consensus methods to functions dependent on pair-wise node attributes and network topology.

Contribution

It proposes a general weighted average consensus algorithm for link-based metrics, including convergence conditions and rate analysis, expanding consensus applications.

Findings

Algorithm successfully computes link-based metrics in distributed settings.

Convergence conditions are established for the proposed method.

Analysis of convergence rate demonstrates efficiency.

Abstract

Average consensus algorithms have wide applications in distributed computing systems where all the nodes agree on the average value of their initial states by only exchanging information with their local neighbors. In this letter, we look into link-based network metrics which are polynomial functions of pair-wise node attributes defined over the links in a network. Different from node-based average consensus, such link-based metrics depend on both the distribution of node attributes and the underlying network topology. We propose a general algorithm using the weighted average consensus protocol for the distributed computation of link-based network metrics and provide the convergence conditions and convergence rate analysis.