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Issue:Generalized net models of queueing disciplines in finite buffer queueing systems with intuitionistic fuzzy evaluations of the tasks

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Title of paper: Generalized net models of queueing disciplines in finite buffer queueing systems with intuitionistic fuzzy evaluations of the tasks
Author(s):
Zhivko Tomov
“Prof. Dr Asen Zlatarov” University, 1 Yakimov Blvd., Burgas 8000, Bulgaria
zhivko57@yandex.ru
Maciej Krawczak
Systems Research Institute, Polish Academy of Sciences, ul. Newelska 6, 01–447 Warsaw, Poland
krawczak@ibspan.waw.pl
Velin Andonov
Institute of Mathematics and Informatics, Bulgarian Academy of Sciences, Acad. Georgi Bonchev Str., bl 8, Sofia 1113, Bulgaria
velin_andonov@math.bas.bg
Krassimir Atanassov
Department of Bioinformatics and Mathematical Modelling, Institute of Biophysics and Biomedical Engineering, Bulgarian Academy of Sciences, Acad. G. Bonchev Str., Bl. 105, Sofia-1113, Bulgaria
Intelligent Systems Laboratory, Prof. Asen Zlatarov University, Bourgas-8010, Bulgaria
krat@bas.bg
Stanislav Simeonov
“Prof. Dr Asen Zlatarov” University, 1 Yakimov Blvd., Burgas 8000, Bulgaria
st_sim@yahoo.com


Published in: Notes on Intuitionistic Fuzzy Sets, Volume 25 (2019), Number 2, pages 115–122
DOI: https://doi.org/10.7546/nifs.2019.25.2.115-122
Download:  PDF (178  Kb, File info)
Abstract: Generalized net models of different queueing disciplines in queueing systems are proposed in [11]. In the present paper, we propose modifications of these models including

Intuitionistic Fuzzy Pairs (IFP) and Interval-Valued Intuitionistic Fuzzy Pairs (IVIFP) which determine the way in which the requests are serviced. In each of the models, the buffer has finite capacity and is represented by two Generalized net transitions. The buffer cells are represented by places of the net. The two simple queueing disciplines considered are FIFO and LIFO. A more general model with IFP (or IVIFP) in which the requests can change their parameters and position within the buffer is also proposed.

Keywords: Generalized net, Queueing system, Queueing discipline, Intuitionistic fuzzy pair.
AMS Classification: 68Q85, 03E72.
References:
  1. Andonov, V., Atanassov, K. (2013). Generalized nets with characteristics of the places.Compt. rend. Acad. bulg. Sci., 66 (12), 1673–1680.
  2. Andonov, V., Poryazov, S., Otsetova, A., & Saranova, E. (2019). A Queue in Overall
  3. Telecommunication System with Quality of Service Guarantees. Proc. of 4th EAI International Conference on Future Access Enablers of Ubiquitous and Intelligent Infrastructures (FABULOUS’2019), Sofia, 28–29 March, 2019 (in press).
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  7. Fuss, H. (1975). P-t-netze zur numerischen simulation von asynchronen fluessen. In: J. Hartmanis G. Goos, editor, GI - 4. Jahrestagung, Berlin 0.-12. Oktober 1974, number 26 in Lecture Notes in Computer Science, 326–335, GI, Gesellschaft fuer Informatik, Springer-Verlag.
  8. Gross, D., Shortle, J., Thompson, J., & Harris, C. (2008). Fundamentals of Queueing Theory, 4th edition. John Wiley & Sons, New York.
  9. Kleinrock, L. (1975). Queueing Systems, Vol. I: Theory. Wiley, New York.
  10. Kleinrock, L. (1976). Queueing Systems, Vol. II: Computer Applications. Wiley, New York.
  11. Poryazov, S., Andonov, V. & Saranova, E. (2018). Comparison of four conceptual models of a queueing system in servicenet works Proc.of 26th NationalConferencewith International Participation TELECOM’2018), Sofia, 25–26 October 2018, 71–77.
  12. Tomov, Zh., Krawczak, M., Andonov, V., Dimitrov, E., &Atanassov, K.(2018).Generalized net models of queueing disciplines in finite buffer queueing systems. Proceedings of 16th International Workshop on Generalized Nets, 10 Feb. 2018, Sofia, 1–9.
  13. Zoteva, D., & Krawczak, M. (2017). Generalized nets as a tool for the modelling of data mining processes. A survey. Issues in Intuitionistic Fuzzy Sets and Generalized Nets, 13, 1–60.
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