Optimizing the Age of Information in Mixed-Critical Wireless Communication Networks

TL;DR

This paper develops an optimization framework for minimizing the age of information in dense B5G IoT networks with mixed-criticality data streams, using advanced mathematical techniques to improve data freshness.

Contribution

It introduces a novel non-convex optimization approach for AoI in mixed-critical IoT networks, employing stochastic reformulations and iterative algorithms for enhanced performance.

Findings

Non-orthogonal transmission outperforms orthogonal schemes in AoI reduction.

The proposed algorithm effectively manages physical transmission and outage probabilities.

Simulation confirms improved AoI and scalability in dense IoT deployments.

Abstract

Beyond fifth generation wireless communication networks (B5G) are applied in many use-cases, such as industrial control systems, smart public transport, and power grids. Those applications require innovative techniques for timely transmission and increased wireless network capacities. Hence, this paper proposes optimizing the data freshness measured by the age of information (AoI) in dense internet of things (IoT) sensor-actuator networks. Given different priorities of data-streams, i.e., different sensitivities to outdated information, mixed-criticality is introduced by analyzing different functions of the age, i.e., we consider linear and exponential aging functions. An intricate non-convex optimization problem managing the physical transmission time and packet outage probability is derived. Such problem is tackled using stochastic reformulations, successive convex approximations, and fractional programming, resulting in an efficient iterative algorithm for AoI optimization. Simulation results validate the proposed scheme's performance in terms of AoI, mixed-criticality, and scalability. The proposed non-orthogonal transmission is shown to outperform an orthogonal access scheme in various deployment cases. Results emphasize the potential gains for dense B5G empowered IoT networks in minimizing the AoI.