Age of Gossip With Cellular Drone Mobility

2026-01-09

arXiv.org

AI Summary

This study investigates the freshness of information in cellular networks where a mobile unmanned aerial vehicle (UAV) disseminates updates to multi-cell nodes, with a focus on the interplay among the number of cells, UAV mobility speed, and update dissemination rate. Leveraging a continuous-time Markov chain to model UAV movement, the work employs version age of information as the metric for timeliness. Theoretical analysis reveals a “dual-bottleneck” effect: the version age is governed by the slower of the two processes—mobility or dissemination. Specifically, under a fully connected mobility model, when the dissemination rate greatly exceeds the mobility speed, the version age depends solely on mobility speed, and vice versa. This work is the first to characterize the scaling laws governing how these two factors jointly influence information freshness, offering foundational insights for timeliness optimization in dynamic networks.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization
• Multiagent Systems: Multiagent Systems under Uncertainty

Application Category

• Social Networks and Social Media: Influence propagation, information diffusion, and the prediction on networks
• Web Mining and Content Analysis: Content-based information diffusion
• User Modeling, Personalization and Recommendation: User privacy protection in personalized systems

Abstract

We consider a cellular network containing $n$ nodes where nodes within a cell gossip with each other in a fully-connected fashion and a source shares updates with these nodes via a mobile drone. The mobile drone receives updates directly from the source and shares them with nodes in the cell where it currently resides. The drone moves between cells according to an underlying continuous-time Markov chain (CTMC). In this work, we evaluate the impact of the number of cells $f(n)$, drone speed $\lambda_m(n)$ and drone dissemination rate $\lambda_d(n)$ on the freshness of information of nodes in the network. We utilize the version age of information metric to quantify the freshness of information. We observe that the expected duration between two drone-to-cell service times depends on the stationary distribution of the underlying CTMC and $\lambda_d(n)$, but not on $\lambda_m(n)$. However, the version age instability in slow moving CTMCs makes high probability analysis for a general underlying CTMC difficult. Therefore, next we focus on the fully-connected drone mobility model. Under this model, we uncover a dual-bottleneck between drone mobility and drone dissemination speed: the version age is constrained by the slower of these two processes. If $\lambda_d(n) \gg \lambda_m(n)$, then the version age scaling of nodes is dominated by the inverse of $\lambda_m(n)$ and is independent of $\lambda_d(n)$. If $\lambda_m(n) \gg \lambda_d(n)$, then the version age scaling of nodes is dominated by the inverse of $\lambda_d(n)$ and is independent of $\lambda_m(n)$.

Problem

• Age of Information
• Mobile Drone
• Cellular Network
• Version Age
• Gossip Protocol

Innovation

• version age of information
• mobile drone
• gossip protocol
• dual-bottleneck
• cellular network