Age of Information with Age-Dependent Server Selection

2025-12-20

AI Summary

This paper addresses the age-of-information (AoI)-minimization problem in single-source multi-server status update systems, where dynamic server selection is performed under transmission cost constraints. We propose a novel discrete-time multi-regime absorbing Markov chain (MR-AMC) analytical framework, enabling the first exact characterization of the steady-state AoI distribution and the joint cost (AoI penalty plus transmission cost). Leveraging phase-type (DPH) service time modeling and a multi-threshold decision policy, we derive a closed-form expression for the constrained bi-objective optimization cost. Optimal multi-threshold policies are obtained via exhaustive search for small-scale systems. Numerical results demonstrate that the proposed policy significantly outperforms static or random server selection schemes. Our work establishes a new analytically tractable and optimization-enabled paradigm for AoI-driven real-time communication resource scheduling.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Multiagent Systems: Agent Communication

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs

Abstract

In this paper, we consider a single-source multi-server generate-at-will discrete-time non-preemptive status update system where update packets are transmitted using {em only one} of the available servers, according to a server selection policy. In particular, when a transmission is complete, the update system makes a threshold-based decision on whether to wait or transmit, and if latter, which server to use for transmissions, on the basis of the instantaneous value of the age of information (AoI) process. In our setting, servers have general heterogeneous discrete phase-type (DPH) distributed service times, and also heterogeneous transmission costs. The goal is to find an age-dependent multi-threshold policy that minimizes the AoI cost with a constraint on transmission costs, the former cost defined in terms of the time average of an arbitrary function of AoI. For this purpose, we propose a novel tool called emph{multi-regime absorbing Markov chain} (MR-AMC) in discrete time. Using the MR-AMC framework, we exactly obtain the distribution of AoI, and subsequently the costs associated with AoI and transmissions. With the exact analysis in hand, optimum thresholds can be obtained in the case of a few servers, by exhaustive search. We validate the proposed analytical model, and also demonstrate the benefits of age-dependent server selection, with numerical examples.

Problem

• Optimizes age-dependent server selection for status updates
• Minimizes Age of Information cost under transmission constraints
• Models heterogeneous server service times and transmission costs

Innovation

• Threshold-based server selection using AoI
• Multi-regime absorbing Markov chain for analysis
• Optimized thresholds for heterogeneous servers and costs