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

2026-02-10

AI Summary

This work addresses the challenge of dynamic blockage caused by mobile obstacles in industrial millimeter-wave multi-hop Integrated Access and Backhaul (IAB) networks, which severely degrades communication reliability and information freshness. To overcome the limitations of conventional packet replication schemes that exacerbate congestion and worsen Age of Information (AoI), this paper proposes RFAS, a novel scheduling algorithm that jointly optimizes AoI and queue stability under packet replication. Leveraging Lyapunov optimization, RFAS transforms the long-term stochastic problem into a sequence of deterministic subproblems, minimizing average AoI while strictly ensuring buffer overflow avoidance. Experimental results demonstrate that RFAS achieves over 95% packet delivery ratio under highly dynamic blockage and heavy traffic loads, reduces load imbalance by 19%, and significantly outperforms existing approaches.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Intelligent Robots: Learning & Optimization for ROB
• Multiagent Systems: Agent Communication

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

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.

Problem

• Industrial mmWave IAB Networks
• Dynamic Blockages
• Packet Duplication
• Age of Information
• Queue Stability

Innovation

• Packet Duplication
• Age of Information
• Lyapunov Optimization
• Queue Stability
• IAB Networks