The purpose of this work is to develop a UJSON web technology with C# application to analyze the student data in real-ime. Execute continuous requests on JSON streaming data based on advanced technologies for parallel streaming computing, suitable for solving analytic problems and calculation of metrics in real-time. The developed management information system in this research work designed to filtering event flow, building an event flow as a query result, grouping and aggregation of events, and creating window semantics. For testing the proposed work, several queries were selected that implement aggregation with different types of semantic windows (Steps, Slides). Testing was done locally and on education moodle clusters. It was used 4 types of configurations 2, 4, 8, and 16 computing nodes. Based on the obtained results, scalability is noticeable with an increase in the number of nodes. The updated functions of the proposed UJSON could improve the construction of parallel flow systems and data processing. The developed approach based on modern and advanced parallel flow technologies for output calculations considering the pros and cons of various approaches found in the current era.
Virtual Streaming Computing Systems with Architecture Based on the Neural Network Information Model
