Numerical Simulation of the Behavior of a Cyberphysical Agent as a Message Queuing System

  • Conference paper
  • First Online:
Cyber-Physical Systems and Control II (CPS&C 2021)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 460))

Included in the following conference series:

  • 434 Accesses

Abstract

The presentation of cyber-physical systems and devices as components of a multi-agent model is considered. The main method of interaction between agents of the cyber-physical type is investigated - the exchange of messages in the multi-agent model. It is proposed to consider the processing of messages from other agents as an indicator of the agent's performance. The dependence of the efficiency indicator of the agent-based model as the probability of timely message processing on the message flow density is analyzed. The technique of numerical modeling of systems with continuous time is considered. For this, the representation of such systems in the form of equivalent signal graphs is used. A technique for constructing such graphs based on a system of differential equations is proposed. A method for joint modeling of dynamic systems and systems with random flows is proposed. A graphic-analytical technique for numerical modeling of a queuing system in the form of a system of inhomogeneous linear differential equations of the first order is considered. An algorithm for the numerical modeling of queuing systems proposed by the authors, based on the previously considered technique, is presented. An example of modeling message processing by the simplest agent in the form of a queuing system is considered. An equivalent numerical simulation graph is constructed, on the basis of which a matrix simulation scheme is obtained. Examples of a simulation experiment and comparison with analytical results are given.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
GBP 19.95
Price includes VAT (United Kingdom)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
GBP 95.50
Price includes VAT (United Kingdom)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
GBP 119.99
Price includes VAT (United Kingdom)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free ship** worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Similar content being viewed by others

References

  1. Schwab, K.: Technologies of the Fourth Industrial Revolution, p. 320. Eksmo, Moscow (2018). (In Russian)

    Google Scholar 

  2. Framework for Cyber-Physical Systems. Volume 1, Overview. https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1500-201.pdf (2017). Last accessed 28 July 2021

  3. Framework for Cyber-Physical Systems. Volume 2, Working Group Reports. https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1500-202.pdf (2017). Last accessed 28 July 2021

  4. Greer, C., Burns, M., Wollman, D., Griffor, E.: Cyber-Physical Systems and Internet of Things. National Institute of Standards and Technology. https://nvlpubs.nist.gov/nistpubs/SpecialPublications/NIST.SP.1900-202.pdf (2019). Last accessed 28 July 2021

  5. Sanfelice, R.: Analysis and design of cyber-physical systems: a hybrid control systems approach (2015)

    Google Scholar 

  6. Lee, E.A., Seshia, S.A.: Introduction to embedded systems—a cyber-physical systems Approach. LeeSeshia.org (2011)

    Google Scholar 

  7. Song, H. Fink, G. A., Jeschke S. (eds.): Security and Privacy in Cyber-Physical Systems. Foundations, Principles, and Applications. Wiley, New Jersey, NJ (2018)

    Google Scholar 

  8. Ventcel, E.S., Ovcharov, L.A.: Tasks and Exercises on Probability Theory. Teaching aid. Vysshaja shkola, Moscow (2000).(In Russian)

    Google Scholar 

  9. Smolov, V.B.: The Analog Computers. Vysshaja shkola, Moscow (1972).(In Russian)

    Google Scholar 

  10. Feldbaum, A.A.: Fundamentals of the Theory of Optimal Automatic Systems. Nauka, Moscow (1966).(In Russian)

    Google Scholar 

  11. Bakusov, L.M., Bakusova, S.M., Nasyrov, R.V.: The algorithm of numerical simulation of systems with continiouse time. Fundamental research, 10–12, 2593–2598 (2013), http://fundamental-research.ru/ru/article/view?id=32836. Last accessed 28 July 2021 (In Russian)

  12. Mathematical encyclopedia, vol. 5, p. 539. Soviet encyclopedia Publ., Moscow (1984). (In Russian)

    Google Scholar 

  13. Bakusov, L.M.: Methods and Models of Casual–Stricter Analysis in Self-organizatiion System Investigation. Mashinostroenie, Moscow (2005). (In Russian)

    Google Scholar 

  14. Nazlı Demir Beh ̧cet A ̧cıkme ̧seCan Pehlivant ̈urk: Density control for decentralized autonomous agents with conflict avoidance. In: Proceedings of the 19th World CongressThe International Federation of Automatic Control, August 24–29, 2014, Cape Town, South Africa, pp. 11715–11721 (2014). https://doi.org/10.13140/2.1.3534.8482

  15. De Wilde, P., Briscoe, G.: Stability of evolving multiagent systems. IEEE Trans Syst Man Cybern B Cybern. 41(4), 1149–1157 (2011). https://doi.org/10.1109/TSMCB.2011.2110642. Epub 2011 Feb 28 PMID: 21356619

    Article  Google Scholar 

  16. Shiba Biswal: Self-organization of multi-agent systems using Markov Chain models, Dissertation for the degree Doctor of Phylosophy, p. 159. Arizona State Unversyti (2020)

    Google Scholar 

  17. Chen, C., Yin, Y.: De Gu1and Fei Liu: Consensus of multi-agent systems with Markov jump topologies and delays. ICIC Express Lett. 12(3), 205–211 (2018)

    Google Scholar 

  18. Wang, H., Zhou, Z., Hu, Z.: Distributed tracking control for discrete-time multiagent systems with novel Markovian switching topologies. Discret. Dyn. Nat. Soc. 2017, 1626452, 10 (2017). https://doi.org/10.1155/2017/1626452

  19. Ruohan Zhang, Yue Yu, Mahmoud El Chamie, Behc ̧et Ac ̧ıkmes ̧e, Dana H. Ballard: Decision-making policies for heterogeneous autonomous multi-agent systems with safety constraints. In: Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (IJC-16), pp.546–552 (2016)

    Google Scholar 

  20. Varma, V., Morarescu, I.-C., Nesic, D.: Open multi-agent systems with discretestates and stochastic interactions. IEEE Control. Syst. Lett. 2(3), 375–380. IEEE (2018). https://doi.org/10.1109/LCSYS.2018.2840431

  21. Banisch, S.: Markov Chain aggregation for agent–based models. Dissertation for the degree Doctor of Phylosophy, p. 166. Max Planck Institute for Mathematics in the Sciences (2014)

    Google Scholar 

  22. Demirer, N.: Density control of multi-agent systems with safety constraints: a Markov Chain approach. Dissertation for the degree Doctor of Phylosophy, p. 153. University of Washington (2017)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Rashit Nasyrov .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Nasyrov, R. (2023). Numerical Simulation of the Behavior of a Cyberphysical Agent as a Message Queuing System. In: Arseniev, D.G., Aouf, N. (eds) Cyber-Physical Systems and Control II. CPS&C 2021. Lecture Notes in Networks and Systems, vol 460. Springer, Cham. https://doi.org/10.1007/978-3-031-20875-1_32

Download citation

  • DOI: https://doi.org/10.1007/978-3-031-20875-1_32

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-20874-4

  • Online ISBN: 978-3-031-20875-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics

Navigation