APPLICATION OF SERVERLESS SYSTEMS FOR PROCESSING METROLOGICAL METADATA IN IOT
Oksana Honsor, Oleksandr Demidov · Measuring Equipment and Metrology · 2024
The article investigates the potential of serverless architectures for efficiently processing large-scale metadata generated by Internet of Things (IoT) sensors. As IoT systems grow increasingly complex, the challenges associated with processing vast amounts of data in distributed environments become more pronounced. Key issues include ensuring data accuracy, maintaining scalability, and reducing the operational costs of data processing infrastructure. The paper proposes serverless computing as a highly adaptable solution to these challenges, focusing on its capacity for real-time processing, dynamic scaling, and seamless integration with modern cloud platforms. The research highlights the importance of dynamic calibration of IoT sensors to ensure the accuracy and reliability of collected data. Dynamic calibration addresses challenges such as environmental changes and sensor degradation, leveraging serverless systems to automate recalibration based on real-time data analysis. The authors propose an architecture based on Amazon Web Services (AWS) to demonstrate the practical application of serverless principles. This architecture incorporates AWS Lambda for computational tasks, SQS for workload distribution, and S3 for scalable data storage. The article emphasises the advantages of serverless systems, including cost-efficiency, resource optimisation, and scalability, while acknowledging challenges such as secure integration of private data and potential errors in automated systems. The authors argue that, with proper implementation, serverless architectures can provide robust solutions for IoT metadata processing, enabling improved performance, reliability, and economic efficiency in modern IoT ecosystems. By addressing both theoretical and practical aspects, the study offers valuable insights for researchers and practitioners seeking to harness the power of serverless systems for IoT applications. The findings underscore the transformative potential of cloud-based, serverless infrastructures in achieving efficient and scalable data management for IoT-driven industries.