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Performance Evaluation of IoT-Based Industrial Automation Using Edge, Fog, and Cloud Architectures

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Udgivet i:Journal of Network and Systems Management vol. 33, no. 1 (Jan 2025), p. 15
Udgivet:
Springer Nature B.V.
Fag:
Data transfer (computers)
Petri nets
Humidity
Design of experiments
Internet of Things
Performance evaluation
Productivity
Data processing
Data analysis
Automation
Manufacturing
Fog
Data collection
Efficiency
Business metrics
Decision support systems
Performance measurement
Edge computing
Sensitivity analysis
Cloud computing
Decision making
Sensors
Resource utilization
Real time
Industry 4.0
Parameters
Agrarian structures
Equipment
Agricultural production
Poultry
Agricultural research
Support networks
Industrial automation
Reaction time
Agricultural technology
Animal husbandry
Internet
Industrial districts
Agriculture
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Resumen:The integration of Internet of Things (IoT) technology into industrial settings has significantly transformed various sectors by automating processes and enhancing decision support systems, thereby boosting productivity and efficiency in agricultural production. This study proposes a Stochastic Petri Net (SPN) model to assess the performance of smart agricultural industrial facilities that integrate Edge, Fog, and Cloud Computing technologies. These technologies utilize sensors to monitor critical operational parameters such as temperature, humidity, and equipment status, enabling efficient data collection, processing, and analysis for informed decision-making and improved operational efficiency. Key challenges include managing large data volumes and ensuring timely data transfer between computing layers, impacting real-time poultry monitoring. The SPN model evaluates key performance metrics, including response time, resource utilization, discard probability, and throughput, while optimizing parameters to enhance system performance and further the application of IoT in industrial automation.
ISSN:1064-7570
1573-7705
DOI:10.1007/s10922-024-09893-x
Fuente:ABI/INFORM Global