Characterizing Information Accuracy in Timeliness-Based Gossip Networks

Fuente: arXiv
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Autori principali: Tekez, Emirhan, Bastopcu, Melih, Gezici, Sinan
Natura: Preprint
Pubblicazione: 2026
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author Tekez, Emirhan
Bastopcu, Melih
Gezici, Sinan
author_facet Tekez, Emirhan
Bastopcu, Melih
Gezici, Sinan
contents We investigate information accuracy in timeliness-based gossip networks where the source evolves according to a continuous-time Markov chain (CTMC) with $M$ states and disseminates status updates to a network of $n$ nodes. In addition to direct source updates, nodes exchange their locally stored packets via gossip and accept incoming packets solely based on whether the incoming packet is fresher than their local copy. As a result, a node can possess the freshest packet in the network while still not having the current source state. To quantify the amount of accurate information flowing in the network under such a gossiping scheme, we introduce two accuracy metrics, average accuracy, defined as the expected fraction of nodes carrying accurate information in any given subset, and freshness-based accuracy, defined as the accuracy of the freshest node in any given subset. Using a stochastic hybrid systems (SHS) framework, we first derive steady-state balance equations and obtain matrix-valued recursions that characterize these metrics in fully connected gossip networks under binary CTMCs. We then extend our analysis to the general multi-state information source using a joint CTMC approach. Finally, we quantify the fraction of nodes whose information is accurate due to direct source pushes versus gossip exchanges. We verify our findings with numerical analyses and provide asymptotic insights.
format Preprint
id arxiv_https___arxiv_org_abs_2603_02197
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Characterizing Information Accuracy in Timeliness-Based Gossip Networks
Tekez, Emirhan
Bastopcu, Melih
Gezici, Sinan
Information Theory
Networking and Internet Architecture
Social and Information Networks
Systems and Control
Signal Processing
We investigate information accuracy in timeliness-based gossip networks where the source evolves according to a continuous-time Markov chain (CTMC) with $M$ states and disseminates status updates to a network of $n$ nodes. In addition to direct source updates, nodes exchange their locally stored packets via gossip and accept incoming packets solely based on whether the incoming packet is fresher than their local copy. As a result, a node can possess the freshest packet in the network while still not having the current source state. To quantify the amount of accurate information flowing in the network under such a gossiping scheme, we introduce two accuracy metrics, average accuracy, defined as the expected fraction of nodes carrying accurate information in any given subset, and freshness-based accuracy, defined as the accuracy of the freshest node in any given subset. Using a stochastic hybrid systems (SHS) framework, we first derive steady-state balance equations and obtain matrix-valued recursions that characterize these metrics in fully connected gossip networks under binary CTMCs. We then extend our analysis to the general multi-state information source using a joint CTMC approach. Finally, we quantify the fraction of nodes whose information is accurate due to direct source pushes versus gossip exchanges. We verify our findings with numerical analyses and provide asymptotic insights.
title Characterizing Information Accuracy in Timeliness-Based Gossip Networks
topic Information Theory
Networking and Internet Architecture
Social and Information Networks
Systems and Control
Signal Processing
url https://arxiv.org/abs/2603.02197