Age of Information in Prioritized Random Access

TL;DR

This paper analyzes how prioritized random access protocols affect the freshness of information, optimizing update strategies to meet AoI requirements while minimizing power use in multi-class device networks.

Contribution

It extends existing AoI analysis to prioritized random access, proposing an optimization of update probabilities and degree distributions for different device classes.

Findings

Optimized update probabilities for AoI constraints.

Derived Markovian models for AoI evolution.

Reduced power consumption while meeting AoI targets.

Abstract

Age of information (AoI) is a performance metric that captures the freshness of status updates. While AoI has been studied thoroughly for point-to-point links, the impact of modern random-access protocols on this metric is still unclear. In this paper, we extend the recent results by Munari to prioritized random access where devices are divided into different classes according to different AoI requirements. We consider the irregular repetition slotted ALOHA protocol and analyze the AoI evolution by means of a Markovian analysis following similar lines as in Munari (2021). We aim to design the protocol to satisfy the AoI requirements for each class while minimizing the power consumption. To this end, we optimize the update probability and the degree distributions of each class, such that the probability that their AoI exceeds a given threshold lies below a given target and the average number of transmitted packets is minimized.