Assisting Mission-Critical Traffic Flows with Active Queue Management in Industrial Internet of Things

2026-07-15

AI Summary

This study addresses the challenge of bufferbloat in industrial Internet of Things (IIoT) networks, where mission-critical traffic suffers from excessive latency and jitter under traditional FIFO queuing, failing to meet stringent deterministic requirements. The work presents the first systematic evaluation of active queue management (AQM) mechanisms in operational technology (OT) domains and proposes a lightweight, non-intrusive multi-queue AQM scheme deployable on commercial off-the-shelf routers. This approach enables effective isolation of critical flows, fair bandwidth sharing, and precise buffer control without requiring modifications to end hosts. Experimental results demonstrate that the proposed solution significantly reduces both latency and jitter for time-sensitive traffic while offering practical configuration guidelines to facilitate real-world deployment in industrial settings.

Abstract

Mission-critical Industrial Internet of Things (IIoT) traffic flows require bounded network latency and jitter guarantees to ensure the safe functioning of critical industrial infrastructure. These flows are typically communicated via commodity network routers with conventional First-In-First-Out (FIFO) buffers. FIFO has proven to be the culprit of the well-known bufferbloat phenomenon, and the deployment of Active Queue Management (AQM) schemes have demonstrated significant performance improvements for latency-sensitive applications over the Internet in the IT domain. However, the bufferbloat phenomenon and the efficacy of AQM schemes have not been studied in IIoT-based OT domain. In this paper, we propose the use of AQM as a lightweight and non-intrusive mechanism for assisting mission-critical traffic flows in IIoT networks. Our experimental results demonstrated that multi-queue AQM schemes provide substantial flow isolation and capacity sharing benefits, and significantly improve the performance of mission-critical traffic flows under network pressure. We further provide deployment recommendations based on our experimental insights.

Problem

• Industrial Internet of Things
• mission-critical traffic
• bufferbloat
• Active Queue Management
• network latency

Innovation

• Active Queue Management
• Industrial Internet of Things
• mission-critical traffic
• bufferbloat
• flow isolation