Minimizing Age of Information in Spatially Distributed Random Access Wireless Networks

TL;DR

This paper investigates how to optimize the freshness of information in spatially distributed wireless networks by designing adaptive transmission policies that minimize various AoI metrics, considering network topology and node locations.

Contribution

It introduces a convex set of achievable AoI, develops location-dependent policies, and proves asymptotic optimality of a simple distance-based policy for large networks.

Findings

AoI can be significantly improved with spatially adaptive policies.

Tight bounds are derived for weighted sum and min-max AoI.

Distance-based policies converge to optimal fairness as network size grows.

Abstract

We analyze Age of Information (AoI) in wireless networks where nodes use a spatially adaptive random access scheme to send status updates to a central base station. We show that the set of achievable AoI in this setting is convex, and design policies to minimize weighted sum, min-max, and proportionally fair AoI by setting transmission probabilities as a function of node locations. We show that under the capture model, when the spatial topology of the network is considered, AoI can be significantly improved, and we obtain tight performance bounds on weighted sum and min-max AoI. Finally, we design a policy where each node sets its transmission probability based only on its own distance from the base station, when it does not know the positions of other nodes, and show that it converges to the optimal proportionally fair policy as the size of the network goes to infinity.