Recommendations for Using QPN Formalism for Preparation of Incoming Request Stream Generator in Modeled System
Source abstract
Abstract
Simulation models are elements of science that use software tools to solve complex mathematical problems. They are beneficial in areas such as performance engineering and communications systems. Nevertheless, to achieve more accurate results, researchers should use more detailed models. Having an analysis of the system operations in the early modeling phases could help one make better decisions relating to the solution. In this paper, we introduce the use of the QPME tool, based on queueing Petri nets, to model the system stream generator. This formalism was not considered during the first tool development. As a result of the analysis, an alternative design model is proposed. By comparing the behavior of the proposed generator against the one already developed, a better adjustment of the stream to the customer’s needs was obtained. The study results show that appropriately adjusting queueing Petri net models can help produce better streams of data (tokens).
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Business Process Modeling and Analysis · Service-Oriented Architecture and Web Services · Simulation Techniques and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Department of Computer and Control Engineering, Rzeszow University of Technology, Powstancow Warszawy 12, 35-959 Rzeszow, Poland
References (23)
Show source-provided references
1. Acquisition and Modeling of Website Parameters
2. Performance Modeling of Database Systems: A Survey
3. Load balancing mechanism using Mobile agents10.31449/inf.v45i2.3230 ↗
4. Walid, B., and Kloul, L. (2019). Formal Models for Safety and Performance Analysis of a Data Center System. Reliab. Eng. Syst. Saf., 193.10.1016/j.ress.2019.106643 ↗
5. Mallick, P.K., Bhoi, A.K., Marques, G., Hugo, C., and de Albuquerque, V. (2021). Formal Techniques for Simulations of Distributed Web System Models. Cognitive Informatics and Soft Computing, Springer.10.1007/978-981-16-1056-1 ↗
6. Fiuk, M., and Czachórski, T. (2019). A Queueing Model and Performance Analysis of UPnP/HTTP Client Server Interactions in Networked Control Systems. Computer Networks (CN 2019), Springer International Publishing AG. Communications in Computer and Information Science.10.1007/978-3-030-21952-9_27 ↗
7. Gaj, P., Sawicki, M., Suchacka, G., and Kwiecień, A. (2018). Consequences of the Form of Restrictions in Coloured Petri Net Models for Behaviour of Arrival Stream Generator Used in Performance Evaluation. Computer Networks, Springer International Publishing.
8. Kounev, S., Lange, K.D., and von Kistowski, J. (2020). Systems Benchmarking: For Scientists and Engineers, Springer International Publishing.10.1007/978-3-030-41705-5 ↗
9. Rak, T. (2020). Modeling Web Client and System Behavior. Information, 11.10.3390/info11060337 ↗
10. Performance Modeling Using Queueing Petri Nets10.1007/978-3-319-59767-6_26 ↗
11. Zatwarnicki, K. (2021). Providing Predictable Quality of Service in a Cloud-Based Web System. Appl. Sci., 11.10.3390/app11072896 ↗
12. Eismann, S., Grohmann, J., Walter, J., von Kistowski, J., and Kounev, S. (2019, January 25–29). Integrating Statistical Response Time Models in Architectural Performance Models. Proceedings of the 2019 IEEE International Conference on Software Architecture (ICSA), Hamburg, Germany.10.1109/ICSA.2019.00016 ↗
13. Roshany, M., and Khorsandi, S. (2018). Performance analysis of the internet-protocol multimedia-subsystem’s control layer using a detailed queueing Petri-net model. Int. J. Commun. Syst., 32.10.1002/dac.3885 ↗
14. Workload Generators for Web-Based Systems: Characteristics, Current Status, and Challenges10.1109/COMST.2018.2798641 ↗
15. Kolbusz, J., Paszczynski, S., and Wilamowski, B. (2005, January 10–12). Network traffic model for industrial environment. Proceedings of the 2005 3rd IEEE International Conference on Industrial Informatics (INDIN’05), Perth, Australia.
16. Modeling and generating realistic streaming media server workloads10.1016/j.comnet.2006.05.003 ↗
17. Formation of equivalent simulation model of an real-time video stream generator used in packet-oriented communication networks, taking into account the structure of the H.264 compression algorithm
18. Huzar, Z., Koci, R., Meyer, B., Walter, B., and Zendulka, J. (2011). HTCPNs–Based Tool for Web–Server Clusters Development. Software Engineering Techniques, Springer.
19. Web–Server Systems HTCPNs-Based Development Tool Application in Load Balance Modelling
20. Bause, F., Buchholz, P., and Kemper, P. (2006). Hierarchically Combined Queueing Petri Nets, Springer.
21. Kounev, S., Spinner, S., and Meier, P. (2012, January 22–25). Introduction to queueing petri nets: Modeling formalism, tool support and case studies. Proceedings of the 3rd Joint WOSP/SIPEW International Conference on Performance Engineering (ICPE’12), Boston, MA, USA.10.1145/2188286.2188290 ↗
22. Kounev, S., Spinner, S., and Meier, P. (2010). QPME 2.0—A Tool for Stochastic Modeling and Analysis Using Queueing Petri Nets, Springer.10.1007/978-3-642-17226-7_18 ↗
23. Rak, T. (2015). Response Time Analysis of Distributed Web Systems Using QPNs. Math. Probl. Eng.10.1155/2015/490835 ↗