Age of Synchronization Minimization in Wireless Networks with Random Updates and Time-Varying Timeliness Requirement

TL;DR

This paper addresses optimizing the freshness of status updates in wireless networks with random arrivals and time-varying importance, using a CMDP framework to develop effective scheduling policies.

Contribution

It introduces a novel CMDP-based approach to minimize weighted Age of Synchronization in networks with dynamic importance levels of updates.

Findings

Proposed policies outperform max-AoS baseline in simulations.

Effective handling of time-varying importance improves freshness.

Near-stationary policies are computationally efficient.

Abstract

This study considers a wireless network where multiple nodes transmit status updates to a base station (BS) via a shared, error-free channel with limited bandwidth. The status updates arrive at each node randomly. We use the Age of Synchronization (AoS) as a metric to measure the information freshness of the updates. The AoS of each node has a timely-varying importance which follows a Markov chain. Our objective is to minimize the weighted sum AoS of the system. The optimization problem is relaxed and formulated as a constrained Markov decision process (CMDP). Solving the relaxed CMDP by a linear programming algorithm yields a stationary policy, which helps us propose a near-stationary policy for the original problem. Numerical simulations show that in most configurations, the AoS performance of our policy outperforms the policy choosing the maximum AoS regardless of weight variations.