Preemption Revisited: Multi-Threshold Preemption Policies for AoI Minimization

TL;DR

This paper develops an analytical framework to evaluate and optimize multi-threshold preemption policies for minimizing Age of Information in systems with random update arrivals, demonstrating their superiority over traditional policies.

Contribution

It introduces a new framework for analyzing multi-threshold preemption policies and shows their effectiveness in reducing AoI compared to existing approaches.

Findings

Multi-threshold policies outperform single-threshold and probabilistic policies.

Significant AoI reductions are achieved by considering both packet age and system age.

Optimal preemption structures have distinctive characteristics revealed by the analysis.

Abstract

The study of optimal preemption policies for status update systems has been a recurring topic in the age of information (AoI) literature, where threshold-based structures have been shown to be optimal under a generate-at-will update generation model under certain assumptions. In this work, we study the effectiveness of threshold-based policies for a system with random update arrivals. In this regard, we introduce an analytical framework for evaluating the AoI of multi-threshold preemption policies and present interesting characteristics of the structure of the optimal preemption policy. We show the effectiveness of these threshold-based policies over the traditional probabilistic preemption policies and single-threshold policies, where we observe that significant gains in terms of AoI can be obtained by utilizing both the age of the packet and the age of the system when designing these preemption policies.