Performance-Based Classification of Users in a Containerized Stock Trading Application Environment Under Load
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| Udgivet i: | Electronics vol. 14, no. 14 (2025), p. 2848-2874 |
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| Hovedforfatter: | |
| Andre forfattere: | , |
| Udgivet: |
MDPI AG
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| Fag: | |
| Online adgang: | Citation/Abstract Full Text + Graphics Full Text - PDF |
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| 001 | 3233143504 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2079-9292 | ||
| 024 | 7 | |a 10.3390/electronics14142848 |2 doi | |
| 035 | |a 3233143504 | ||
| 045 | 2 | |b d20250101 |b d20251231 | |
| 084 | |a 231458 |2 nlm | ||
| 100 | 1 | |a Rak Tomasz |u Department of Computer and Control Engineering, Rzeszow University of Technology, Powstancow Warszawy 12, 35-959 Rzeszow, Poland; jdrabek@prz.edu.pl | |
| 245 | 1 | |a Performance-Based Classification of Users in a Containerized Stock Trading Application Environment Under Load | |
| 260 | |b MDPI AG |c 2025 | ||
| 513 | |a Journal Article | ||
| 520 | 3 | |a Emerging digital technologies are transforming how consumers participate in financial markets, yet their benefits depend critically on the speed, reliability, and transparency of the underlying platforms. Online stock trading platforms must maintain high efficiency underload to ensure a good user experience. This paper presents performance analysis under various load conditions based on the containerized stock exchange system. A comprehensive data logging pipeline was implemented, capturing metrics such as API response times, database query times, and resource utilization. We analyze the collected data to identify performance patterns, using both statistical analysis and machine learning techniques. Preliminary analysis reveals correlations between application processing time and database load, as well as the impact of user behavior on system performance. Association rule mining is applied to uncover relationships among performance metrics, and multiple classification algorithms are evaluated for their ability to predict user activity class patterns from system metrics. The insights from this work can guide optimizations in similar distributed web applications to improve scalability and reliability under a heavy load. By framing performance not merely as a technical property but as a determinant of financial decision-making and well-being, the study contributes actionable insights for designers of consumer-facing fintech services seeking to meet sustainable development goals through trustworthy, resilient digital infrastructure. | |
| 653 | |a Big Data | ||
| 653 | |a Machine learning | ||
| 653 | |a User behavior | ||
| 653 | |a Performance measurement | ||
| 653 | |a Data mining | ||
| 653 | |a Classification | ||
| 653 | |a Applications programs | ||
| 653 | |a Reliability | ||
| 653 | |a Design | ||
| 653 | |a Data analysis | ||
| 653 | |a Data collection | ||
| 653 | |a User experience | ||
| 653 | |a Sustainable development | ||
| 653 | |a Automation | ||
| 653 | |a Stock exchanges | ||
| 653 | |a Resource utilization | ||
| 653 | |a Statistical analysis | ||
| 653 | |a Workloads | ||
| 653 | |a Response time (computers) | ||
| 653 | |a Business metrics | ||
| 653 | |a Data logging | ||
| 700 | 1 | |a Drabek, Jan |u Department of Computer and Control Engineering, Rzeszow University of Technology, Powstancow Warszawy 12, 35-959 Rzeszow, Poland; jdrabek@prz.edu.pl | |
| 700 | 1 | |a Charytanowicz Małgorzata |u Department of Computer Science, Lublin University of Technology, Nadbystrzycka 36B, 20-618 Lublin, Poland; m.charytanowicz@pollub.pl | |
| 773 | 0 | |t Electronics |g vol. 14, no. 14 (2025), p. 2848-2874 | |
| 786 | 0 | |d ProQuest |t Advanced Technologies & Aerospace Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3233143504/abstract/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text + Graphics |u https://www.proquest.com/docview/3233143504/fulltextwithgraphics/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |
| 856 | 4 | 0 | |3 Full Text - PDF |u https://www.proquest.com/docview/3233143504/fulltextPDF/embedded/L8HZQI7Z43R0LA5T?source=fedsrch |