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

This article 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 multirate 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 (2P) 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 (OA) and repetitive scheduling (RS). OA performs simple and effective packet aggregation, enhancing schedulability by up to 97% and reducing execution time by up to 29%, in our simulation. RS 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.

Authors

Institutions

Publication Details

Journal
IEEE Sensors Journal
Published
2025-01-01
DOI
https://doi.org/10.1109/jsen.2025.3568167
Primary Topic
Network Time Synchronization Technologies
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

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

Luis F. Abanto‐Leon, Dingwen Yuan, Matthias Hollick
IEEE Sensors Journal
Network Time Synchronization Technologies
article

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

Luis F. Abanto‐Leon, Dingwen Yuan, Matthias Hollick
article en

Abstract

This article 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 multirate 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 (2P) 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 (OA) and repetitive scheduling (RS). OA performs simple and effective packet aggregation, enhancing schedulability by up to 97% and reducing execution time by up to 29%, in our simulation. RS 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.

IEEE Sensors Journal
Technische Universität Darmstadt (DE)
Affordable and clean energy
Openalex Percentile: Top 90%
Network Time Synchronization Technologies
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.