INTEGRATION OF DECENTRALIZED PERFORMANCE VERIFICATION IN HYBRID ARCHITECTURES EDGE-FOG-CLOUD TO INCREASE IoT SYSTEMS RELIABILITY

Roman Diachok, Halyna Klym

Abstract


Background. The rapid growth of Internet of Things (IoT) systems has increased the demand for scalable and low-latency data processing architectures. Traditional cloud-centric approaches often suffer from high communication delays and bandwidth limitations. Edge–Fog–Cloud computing introduces a multi-tier model that distributes computational tasks closer to data sources. However, evaluating computational methods in such heterogeneous environments requires systematic performance analysis and architectural optimization. In this context, integrating mathematically stable and computationally efficient methods, such as harmonic potential field–based approaches, is essential to ensure reliable real-time operation, scalability, and system resilience across distributed layers.

Methods. This study evaluates the Laplace artificial potential field method implemented within a multi-tier Edge–Fog–Cloud architecture. The experimental framework includes distributed simulation, real-time processing scenarios, and comparative benchmarking. Performance metrics such as latency, computational load, and system stability were analyzed. The proposed approach was tested under variable workload conditions to assess scalability and efficiency across architectural layers.

Results and Discussion. Experimental results demonstrate reduced end-to-end latency and improved task distribution across edge and fog layers. Compared to centralized processing, the proposed architecture maintains stability under increased workload. The Laplace-based computational model ensures efficient obstacle handling and balanced resource utilization. These findings confirm that multi-tier orchestration enhances system responsiveness while preserving acceptable computational overhead in dynamic IoT environments.

Conclusion. Integrating the Laplace artificial potential field method within an Edge–Fog–Cloud architecture significantly improves distributed system performance. The proposed framework increases scalability, reliability, and computational efficiency in real-time IoT applications, providing a solid foundation for further optimization of resource management and intelligent task allocation in heterogeneous distributed environments.

Keywords: Edge–Fog–Cloud; IoT; Laplace artificial potential field; distributed computing; real-time processing; latency; runtime verification.


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References


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DOI: http://dx.doi.org/10.30970/eli.33.15

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