Latency Aware Edge Architectures for Industrial IoT: Design Patterns and Deterministic Networking Integration - Harriz, Muhammad Alfathan (Indonesian Scientific Publication, 2025)
This study explores the design patterns and latency budgets required for real time performance in edge based Industrial Internet of Things (IIoT) systems. As industrial applications increasingly demand ultra low latency for control loops and automation tasks, cloud computing architectures fall short in meeting strict timing requirements. The research investigates architectural configurations such as on premises edge computing, hybrid edge↔cloud frameworks, and 5G Multi access Edge Computing (MEC), all integrated with deterministic networking technologies like Time Sensitive Networking (TSN). The methodology includes modeling latency partitions across communication, computation, and execution layers, evaluating IIoT protocols such as OPC UA PubSub and MQTT Sparkplug B, and measuring metrics like end to end latency, jitter, and deadline miss percentages under realistic workloads. Results confirm that edge architectures, when combined with TSN and real-time operating environments, can achieve latency budgets as low as approximately 1 millisecond (ms) for servo loops and between 6–12 ms for machine vision tasks. These values highlight the feasibility of meeting industrial automation requirements. The conclusion underscores the importance of matching communication technologies wired TSN versus 5G URLLC according to environmental constraints and specific application requirements. It also emphasizes the role of hybrid architectures and standardized protocols in enabling scalable, interoperable, and deterministic IIoT systems. This work contributes a validated framework for deploying real time industrial systems capable of meeting the performance thresholds of Industry 4.0.