Ismail’s contemporary pointwise stationary fluid approximation theory: Discovering the unknown transitions between stability, traffic intensity, and chaos of the nonstationary  queueing system

Authors

  • Ismail A Mageed * PhD, AIMMA, IEEE, IAENG, School of Computer Science, AI, and Electronics, Faculty of Engineering and Digital Technologies, University of Bradford, United Kingdom. https://orcid.org/0000-0002-3691-0773
  • Abdul Raheem Nazir Department of Computing, Sheffield Hallam University, Sheffield, South Yorkshire, United Kingdom.

https://doi.org/10.48313/mtei.v2i1.37

Abstract

This research investigates the unexplored domain of negative  parameters within dynamic systems, focusing on their influence across stability, traffic intensity, and chaotic phases. Using an iterative computational framework, we examine the sigma function (σ) to characterize system responses under varying conditions of  and Visualizations and insights demonstrate transitions between phases for a first-ever exploration of negative values of the number of phases (k), with novel findings that extend foundational studies. This work establishes a baseline for further explorations of negative parameter spaces in complex systems. It is worth noting that the current work makes new contributions to Ismail’s contemporary Pointwise Stationary Fluid Approximation (PSFFA) theory by providing a comprehensive computational framework for exploring dynamic system behavior across varying parameter values.

Keywords:

Pointwise stationary fluid approximation, The nonstationary E-k/M/1 queue, k sets of phases

References

  1. [1] A Mageed, I. (2024). Effect of the root parameter on the stability of the non-stationary D/M/1 queue’s GI/M/1 model with PSFFA applications to the internet of things (IoT). Journal of sensor networks and data communications, 4(1), 01-09. https://B2n.ir/rx3522

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Published

2025-03-27

How to Cite

A Mageed, I., & Nazir, A. R. (2025). Ismail’s contemporary pointwise stationary fluid approximation theory: Discovering the unknown transitions between stability, traffic intensity, and chaos of the nonstationary  queueing system. Mechanical Technology and Engineering Insights, 2(1), 41-49. https://doi.org/10.48313/mtei.v2i1.37

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