Reliability Evaluation of RSrSF-LoRa and LoRaWAN for Dense Industrial IoT Networks in a Smelter Environment
Abstract
Industrial Internet of Things (IIoT) systems are increasingly deployed in heavy industrial facilities to support real-time monitoring, automation, and safety-critical operations. Long-range low-power communication technologies such as LoRaWAN are widely used for large-scale sensor connectivity due to their long communication range and energy efficiency. However, dense industrial deployments may experience reduced communication reliability due to network congestion, packet collisions, and challenging propagation conditions caused by metallic infrastructure and electromagnetic interference. To address these limitations, this paper proposes RSrSF-LoRa, an integrated implementation of the reserved spreading factor (rSF) mechanism within the RS-LoRa framework (lightweight scheduling), designed to improve reliability for critical traffic. The study presents a comparative performance evaluation of RSrSF-LoRa and LoRaWAN in a smelter IIoT deployment, assessing packet delivery ratio (PDR), throughput, fairness, energy consumption and scalability under varying node densities and gateway configurations. Single-gateway scenarios with 100, 500, and 1000 nodes, and seven-gateway scenarios with 1000 and 2100 nodes, are evaluated as communication distances increase. The results indicate that while throughput and fairness remain comparable across approaches, RSrSF-LoRa improves alarm message reliability in dense single-gateway deployments, extending the acceptable PDR from 700 m to 900 m.…
Read the paper
Related studies
- The Matrisome: In Silico Definition and In Vivo Characterization by Proteomics of Normal and Tumor Extracellular Matrices
- The Escherichia coli MG1655 in silico metabolic genotype: Its definition, characteristics, and capabilities
- In silico pharmacology for drug discovery: methods for virtual ligand screening and profiling
- In silico prediction of splice-altering single nucleotide variants in the human genome
- In silico clinical trials: how computer simulation will transform the biomedical industry
- In silico optimization of a guava antimicrobial peptide enables combinatorial exploration for peptide design
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.