Transactions on Mass-Data Analysis of Images and Signals P-ISSN1868-6451, E-ISSN 2509-9353, ISBN 978-3-942952-88-0
Volume 12 - Number 1 - September 2021 - Page 3-11
Discrete Event Model of Pandemic Data Processing
Calin Ciufudean
Stefan cel Mare University, Suceava, 720229, Romania
Abstract
Big data processing issues is a key response against the critical situations like pandemic one. Processing pandemic data is directly related to control the asynchronous flow of big data therefore this paper is focused on modeling such technical issue using discrete event formalisms, i.e. Petri nets. The techniques of the usual Petri nets require that the designer should be able to represent the Petri structures on the basis of the structural and functional properties of the modeled systems. Applications that are limited to simple systems have already shown that this goal is not easy to accomplish. Therefore, all these approaches have a more academic value, although they provide a schematic framework for the construction of practical models. A Petri net unitary scheme is preferred to represent the overall and control plans for better integration of the final data. A theoretical model is proposed here.
Keywords: Big Data, Pandemic, Petri Nets, Data Slots, Discrete Event Model, Critical Data String.
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