Performance Evaluation of an API Stock Exchange Web System on Cloud Docker Containers

Author:

Rak Tomasz1ORCID

Affiliation:

1. Department of Computer and Control Engineering, Rzeszow University of Technology, Powstancow Warszawy 12, 35-959 Rzeszow, Poland

Abstract

This study aims to identify the most effective input parameters for performance modelling of container-based web systems. We introduce a method using queueing Petri nets to model web system performance for containerized structures, leveraging prior measurement data for resource demand estimation. This approach eliminates intrusive interventions in the production system. Our research evaluates the accuracy of various formal estimation methods, pinpointing the most suitable for container environments. With the use of a stock exchange web system benchmark for data collection and simulation verification, our findings reveal that the proposed method ensures precise response time parameter accuracy for such architectural configurations.

Publisher

MDPI AG

Subject

Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science

Reference42 articles.

1. Rak, T. (2021). Cognitive Informatics and Soft Computing, Springer.

2. An Effective Classification-Based Framework for Predicting Cloud Capacity Demand in Cloud Services;Xia;IEEE Trans. Serv. Comput.,2021

3. Prediction of Cloud Resources Demand Based on Hierarchical Pythagorean Fuzzy Deep Neural Network;Chen;IEEE Trans. Serv. Comput.,2021

4. Rak, T., and Żyła, R. (2022). Using Data Mining Techniques for Detecting Dependencies in the Outcoming Data of a Web-Based System. Appl. Sci., 12.

5. Performance Modeling Using Queueing Petri Nets;Rak;Computer Networks, Proceedings of the 24th International Conference on Computer Networks, Ladek Zdroj, Poland, 20–23 June 2017,2017

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