Reference:
Cherepenin V.A., Smyk N.O., Vorob'ev S.P..
Integration of cloud, fog, and edge technologies for the optimization of high-load systems
// Software systems and computational methods. – 2024. – ¹ 1.
– P. 1-9.
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Abstract: The study is dedicated to analyzing methods and tools for optimizing the performance of high-load systems using cloud, fog, and edge technologies. The focus is on understanding the concept of high-load systems, identifying the main reasons for increased load on such systems, and studying the dependency of the load on the system's scalability, number of users, and volume of processed data. The introduction of these technologies implies the creation of a multi-level topological structure that facilitates the efficient operation of distributed corporate systems and computing networks. Modern approaches to load management are considered, the main factors affecting performance are investigated, and an optimization model is proposed that ensures a high level of system efficiency and resilience to peak loads while ensuring continuity and quality of service for end-users. The methodology is based on a comprehensive approach, including the analysis of existing problems and the proposal of innovative solutions for optimization, the application of architectural solutions based on IoT, cloud, fog, and edge computing to improve performance and reduce delays in high-load systems. The scientific novelty of this work lies in the development of a unique multi-level topological structure capable of integrating cloud, fog, and edge computing to optimize high-load systems. This structure allows for improved performance, reduced delays, and effective system scaling while addressing the challenges of managing large data volumes and servicing multiple requests simultaneously. The conclusions of the study highlight the significant potential of IoT technology in improving production processes, demonstrating how the integration of modern technological solutions can contribute to increased productivity, product quality, and risk management.
Keywords: Technology integration, Internet of Things, Scalability, Performance optimization, Edge computing, Fog computing, Cloud computing, High-load systems, Data management, Service continuity
References:
Catal, C. (2019). Tekinerdogan, B. Aligning education for the life sciences domain to support digitalization and Industry 4.0. Procedia Computer Science. 158, 99–106. doi:10.1016/j.procs.2019.09.032
Patel, C. (2020). Doshi, N. A novel MQTT security framework in generic IoT model. Procedia Computer Science. 171, 1399–1408. doi:10.1016/j.procs.2020.04.150
Subeesh, A., Mehta, C.R. (2021). Automation and digitization of agriculture using artificial intelligence and internet of things. Artificial Intelligence in Agriculture. 5, 278–291. doi:10.1016/j.aiia.2021.11.004
Faridi, F., Sarwar, H., Ahtisham, M., Kumar, S., Jamal, K. (2022). Cloud computing approaches in health care. Materials Today: Proceedings. 51, 1217–1223. doi:10.1016/j.matpr.2021.07.210
Tzounis, A., Katsoulas, N., Bartzanas, T., Kittas, C. (2017). Internet of Things in agriculture, recent advances and future challenges. Biosystems Engineering. 164, 31–48. doi:10.1016/j.