Resilient and Freshness-Aware Scheduling for Industrial Multi-Hop IAB Networks: A Packet Duplication Approach

TL;DR

This paper introduces RFAS, a scheduling algorithm for industrial mmWave IAB networks that balances reliability and freshness by optimizing packet duplication and queue stability.

Contribution

It formulates a novel optimization problem and proposes RFAS, a resilient scheduling algorithm that guarantees queue stability and improves network performance in blockage-prone environments.

Findings

RFAS maintains PDR above 95% in blockage scenarios.

RFAS guarantees queue stability under buffer constraints.

RFAS reduces load imbalance by 19% in high-traffic scenarios.

Abstract

In industrial millimeter-wave (mmWave) multi-hop Integrated Access and Backhaul (IAB) networks, dynamic blockages caused by moving obstacles pose a severe threat to robust and continuous networks. While Packet Duplication (PD) enhances reliability by path diversity, it inevitably doubles the traffic load, leading to severe congestion and degraded Age of Information (AoI). To navigate this reliability-congestion trade-off, we formulated an optimization problem in a multi-hop IAB scenario that minimizes the average AOI while satisfying strict queue stability constraints. We utilize Lyapunov optimization to transform the long-term stochastic optimization problem into tractable deterministic sub-problems. To solve these sub-problems efficiently, we propose a Resilient and Freshness-Aware Scheduling (RFAS) algorithm. Simulation results show that in blockage-prone environments, RFAS significantly outperforms baselines by maintaining a Packet Delivery Ratio (PDR) above 95\%. Crucially, it strictly guarantees queue stability under hard buffer constraints, whereas baselines suffer from buffer overflows. Furthermore, RFAS reduces the network load imbalance by 19\% compared to the baseline in high-frequency traffic scenarios. This confirms RFAS as a robust and sustainable solution for real-time industrial control loops.