Optimizing Information Freshness in Broadcast Network with Unreliable Links and Random Arrivals: An Approximate Index Policy

TL;DR

This paper develops an approximate index scheduling policy to optimize information freshness in broadcast networks with unreliable links and stochastic update arrivals, demonstrating near-optimal performance through simulations.

Contribution

It introduces a novel approximate index policy for AoI minimization considering unreliable links and stochastic arrivals, extending previous models.

Findings

The proposed policy achieves near-optimal AoI performance.

Simulation results validate the effectiveness of the approximate index approach.

The model generalizes previous work by incorporating unreliable links and random arrivals.

Abstract

With the rapid growth of real-time Internet of Things (IoT) applications, the need for fresh information has surged. Age of Information (AoI) is a tailor-made metric to characterize the information freshness perceived by the devices. In this paper, we investigate the problem of scheduling updates to minimize AoI in broadcast network. In this case, a central controller, e.g. a base station, collects status updates from different sources and schedules them to corresponding clients. Different from previous work, we consider both stochastic status updates and unreliable links. The problem is first modeled as an infinite horizon average constrained cost Markov decision problem (CMDP). With Lagrangian relaxation, an approximation of Whittle's index is derived and a scheduling policy is designed based on the approximate index. The results in previous work can be view as degenerate cases of the approximation index policy either with reliable links or periodic arrival constraints. Simulation results demonstrate the near-optimal performance of the proposed policy.