Scheduling Mechanisms in Wireless Sensor-Actuator Networks for Multi-rate Periodic Control in Industry 4.0

2026-05-28

AI Summary

This study addresses the real-time scheduling challenges in resource-constrained wireless sensor-actuator networks under multi-rate periodic control in Industry 4.0. The authors propose a unified framework integrating two-stage scheduling, the LLF-RC algorithm, opportunistic aggregation, and repetitive scheduling. This framework is the first to simultaneously ensure high reliability and schedulability while significantly reducing actuation latency, communication overhead, and memory requirements. Specifically, the LLF-RC algorithm balances scheduling performance with low computational complexity, opportunistic aggregation enhances scheduling efficiency, and repetitive scheduling drastically curtails resource consumption. Simulation results demonstrate that opportunistic aggregation improves schedulability by up to 97% and reduces execution time by 29%, while repetitive scheduling lowers the worst-case execution time by 92% and cuts both communication and storage costs by 99%.

Abstract

This paper investigates scheduling strategies for wireless sensor-actuator networks (WSANs) in Industry 4.0 scenarios. In particular, we address the problem of real-time scheduling for multi-rate control systems by proposing a novel framework. Our framework features four strategies that improve reliability, schedulability and execution time, and reduce communication and storage costs. Two-phase scheduling is our first strategy, devised to improve communication reliability. Our second strategy is the least-laxity-first with remaining conflicts (LLF-RC) scheduling algorithm, which has high schedulability and affordable execution time. LLF-RC also keeps the maximum queue length at a moderate level, making it suitable for storage-constrained devices. Our third and fourth strategies are opportunistic aggregation and repetitive scheduling. Opportunistic aggregation performs simple and effective packet aggregation, enhancing schedulability by up to 97% and reducing execution time by up to 29%, in our simulation. Repetitive scheduling has negligible execution time, and contributes to minimize communication and storage costs. It reduces the maximum execution time by 92% and the maximum communication and storage cost by 99%, in our simulation. We compare our proposed framework against existing approaches, and evaluate the advantages of our strategies in realistic scenarios.

Problem

• Wireless Sensor-Actuator Networks
• Multi-rate Periodic Control
• Real-time Scheduling
• Industry 4.0
• Schedulability

Innovation

• Wireless Sensor-Actuator Networks
• Multi-rate Periodic Control
• LLF-RC Scheduling
• Opportunistic Aggregation
• Repetitive Scheduling