MODELING AND DEBUGGING OF MEASUREMENT DATA PROCESSING ALGORITHMS
DOI:
https://doi.org/10.65164/b7dqx632Kalit so‘zlar:
Edge computing, Fog computing, measurement systems, data processing, Petri nets, algorithm verification, distributed computing, debugging, modeling.Abstrak
This paper presents an approach to the verification and debugging of measurement
data processing algorithms in systems based on Edge and Fog computing architectures. A practical
case study demonstrates the behavior of measured parameters under error conditions occurring at
different levels of distributed data processing— both at peripheral (Edge) devices and intermediate
(Fog) nodes. The impact of latency, partial data loss, and incorrect signal preprocessing on real-time
measurement results is analyzed. Methods for error detection and localization using formal
512
mathematical tools, in particular Petri nets, are presented, enabling the modeling of distributed
computational processes. The main types of errors arising in decentralized processing environments
are examined, along with their interpretation through the properties of Petri nets. The proposed
approach improves the reliability, robustness, and accuracy of measurement systems by enabling early
detection and correction of errors at the Edge and Fog computing levels.
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