Gossiping with Binary Freshness Metric

TL;DR

This paper analyzes the binary freshness metric in various gossip network topologies, developing recursive equations via SHS, and explores how network structure and size affect information freshness.

Contribution

It introduces a recursive SHS-based framework for binary freshness in arbitrary gossip networks and characterizes its behavior in different structured topologies.

Findings

Binary freshness decreases as n^{-1} in disconnected and ring networks.

In ring networks, binary freshness remains strictly larger than in disconnected networks.

Fully connected networks exhibit a slower decay, approximately n^{- ho} with bla<1, under high update rates.

Abstract

We consider the binary freshness metric for gossip networks that consist of a single source and $n$ end-nodes, where the end-nodes are allowed to share their stored versions of the source information with the other nodes. We develop recursive equations that characterize binary freshness in arbitrarily connected gossip networks using the stochastic hybrid systems (SHS) approach. Next, we study binary freshness in several structured gossip networks, namely disconnected, ring and fully connected networks. We show that for both disconnected and ring network topologies, when the number of nodes gets large, the binary freshness of a node decreases down to 0 as $n^{-1}$, but the freshness is strictly larger for the ring topology. We also show that for the fully connected topology, the rate of decrease to 0 is slower, and it takes the form of $n^{-\rho}$ for a $\rho$ smaller than 1, when the update rates of the source and the end-nodes are sufficiently large. Finally, we study the binary freshness metric for clustered gossip networks, where multiple clusters of structured gossip networks are connected to the source node through designated access nodes, i.e., cluster heads. We characterize the binary freshness in such networks and numerically study how the optimal cluster sizes change with respect to the update rates in the system.