Preemption Revisited: Multi-Threshold Preemption Policies for AoI Minimization
For network designers managing status updates, this work provides improved preemption policies that reduce AoI, though the improvement is incremental over existing threshold-based approaches.
This paper studies multi-threshold preemption policies for minimizing age of information (AoI) in status update systems with random arrivals, showing significant AoI gains over traditional probabilistic and single-threshold policies.
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.