Characterizing Information Accuracy in Timeliness-Based Gossip Networks

2026-03-02

AI Summary

This work addresses the challenge of information accuracy in age-aware gossip networks, where nodes accept updates solely based on freshness, potentially propagating the latest but inaccurate states. The paper introduces the first formal metrics for quantifying accuracy in such protocols—namely, average accuracy and freshness-weighted accuracy. By developing a unified framework combining stochastic hybrid systems (SHS) and joint continuous-time Markov chains (CTMCs), and leveraging matrix recurrences alongside asymptotic analysis, the authors derive closed-form expressions for the steady-state accuracy in fully connected networks with both binary and multi-state dynamic sources. The analytical results explicitly quantify the respective contributions of direct pushes and gossip exchanges to overall accuracy, and extensive simulations confirm the theoretical predictions.

Technology Category

• Multiagent Systems: Multiagent Systems under Uncertainty
• Reasoning under Uncertainty: Stochastic Optimization
• Planning, Routing, and Scheduling: Scheduling under Uncertainty

Application Category

• Social Networks and Social Media: Influence propagation, information diffusion, and the prediction on networks
• Security and Privacy: Large-scale security measurements
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

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.

Problem

• information accuracy
• gossip networks
• timeliness
• Markov chain
• freshness

Innovation

• information accuracy
• timeliness-based gossip
• stochastic hybrid systems (SHS)
• continuous-time Markov chain (CTMC)
• freshness-based accuracy