Skip to main content

G-Networks: A Survey of Results, a Solver and an Application

  • Chapter

Part of the book series: Esprit Basic Research Series ((ESPRIT BASIC))

Summary

In this paper, we first present a brief survey of the main theoretical results providing product forms for networks of queues with positive and negative customers and with signals (G-networks). Then we present a graphical tool for solving a G-network model in steady state, i.e. for finding the steady-state probabilities of the number of positive customers in a G-network. The user will draw a G-network on the screen and input the parameters of each queue (mean service time, arrival rates, routing probabilities, etc.). Then the solver will provide the user with the solution of the system of non-linear traffic equations, and the stationary distribution of queue length, and performance measures such as sojourn times, mean number of customers in the system. Finally we show how these theoretical results and the tool we describe can be used to obtain an analytical solution to a problem which until now has resisted to such a treatment: the performance evaluation of receiver initiated load balancing algorithms in distributed systems.

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. J. Aguilar, “Comparison between the Random Neural Network Model and other Optimization Combinatorial Methods for the Large Acyclic Graph Partitioning Problem”, Proc. 7th Int. Symp. on Computer and Information Sciences (ISCIS), Antalya, Turkey, 1992.

    Google Scholar 

  2. J. Aguilar, “L’allocation de tâches, l’équilibrage de charge et l’optimisation combinatoire”, PhD Thesis, University of Paris V, France, 1995.

    Google Scholar 

  3. V. Atalay, “Réseaux de neurones aléatoires et textures d’images”, PhD Thesis, University of Paris V, France, Nov. 1993.

    Google Scholar 

  4. V. Atalay, E. Gelenbe and N. Yalabik, “Image Texture Generation with the Random Neural Network Model”, Int. Conf. on Artificial Neural Networks (ICANN-91), Helsinki (Kohonen T. ed.), Elsevier, 1991.

    Google Scholar 

  5. F. Baskett, K.M. Chandy, R.R. Muntz and F.G. Palacios, “Open, Closed and Mixed Networks of Queues with Different Classes of Customers”, Journal of ACM, 22(2), pp. 248–260, Apr. 1975.

    Article  MathSciNet  MATH  Google Scholar 

  6. R. Boucherie, “Product-form in queueing networks”, PhD thesis, Vrije Universiteit, North-Holland, May 1992.

    Google Scholar 

  7. R. Boucherie and N. Van Dijk, “Local Balance in queueing networks with negative customers”, Research memorandum 1992–1, Free University of Amsterdam, North-Holland, 1992.

    Google Scholar 

  8. J-M. Fourneau, “Computing the Steady-state Distribution of Networks with Positive and Negative Customers”, LRI Report, 13th XS IMACS World Congress on Computation and Applied Mathematics, Dublin, Ireland, 1991.

    Google Scholar 

  9. J-M. Fourneau and E. Gelenbe, “G-Networks with Multiple Classes of Signals”, Proceedings ORSA Computer Science Technical Committee Conference, Williamsburgh, VA, USA, Jan. 8–10, Pergamon Press, 1992.

    Google Scholar 

  10. J-M. Fourneau and E. Gelenbe, “Multiclass G-Networks”, ORSA Conference: Computer Science and operation Research: new developments in their interface, Williamsburg, USA, Jan. 1992.

    Google Scholar 

  11. J-M. Fourneau, L. Kloul and F. Quessette, “Multiple Class G-Networks with Jumps back to Zero”, Proc. of the 3d Int. Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS’95), Durham, NC, USA, pp. 28-32, Jan. 1995.

    Google Scholar 

  12. J-M. Fourneau and D. Verchère, “G-Networks with Triggered Batch State Dependent Movement”, Proc. of the 3d Int. Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS’95), Durham, NC, USA, pp. 33-37, Jan. 1995.

    Google Scholar 

  13. E. Gelenbe, “Random Neural Networks with Negative and Positive Signals and Product Form Solution”, Neural Computation, 1(4), pp. 502–510, 1989.

    Article  Google Scholar 

  14. E. Gelenbe, “Réseaux Stochastiques avec Clients Négatifs et Positifs et Réseaux Neuronaux”, Comptes-Rendus Académie des Sciences, 309, Série II, Paris, France, pp.979-982, 1989.

    Google Scholar 

  15. E. Gelenbe, “Réseaux Neuronaux Aléatoires Stables”, Comptes-Rendus Académie des Sciences, Paris, France, pp. 310–313, 1990.

    Google Scholar 

  16. E. Gelenbe, “Stability of the Random Neural Network Model”, Neural Computation, 2(2), pp. 239–247, 1990.

    Article  Google Scholar 

  17. E. Gelenbe, “Product Form Queueing Networks with Positive and negative customers”, Journal of Applied Probability, 28, pp. 656–663, 1991.

    Article  MathSciNet  MATH  Google Scholar 

  18. E. Gelenbe, “Theory of the Random Neural Network Model”, Neural Networks: Advances and Applications (E. Gelenbe ed.), North-Holland, 1991.

    Google Scholar 

  19. E. Gelenbe, “G-Nets and Learning Recurrent Random Networks”, Proc. Int. Conf. on Artificial Neural Networks, Brighton, England, 1992.

    Google Scholar 

  20. E. Gelenbe, “G-Networks: A Unifying Model for Neural Nets and Queueing Networks”, Proc. of the 1st Int. Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTS’93), San Diego, CA, USA, Simulation Series, 25(1), pp. 3–8, 1993.

    Google Scholar 

  21. E. Gelenbe, “G-Networks with Triggered Customer Movement”, Journal of Applied Probability, 30, pp. 742–748, 1993.

    Article  MathSciNet  MATH  Google Scholar 

  22. E. Gelenbe, “G-Networks with Signals and Batch Removals”, Probability in Engineering and Informational Sciences, Cambridge University Press, England, 7, pp. 335–342, 1993.

    Google Scholar 

  23. E. Gelenbe, “Learning in the Recurrent Random Neural Network”, Neural Computation, 5(5), pp. 154–164, 1993.

    Article  Google Scholar 

  24. E. Gelenbe, “G-networks and Minimum Cost Functions”, Proc. of the 3d Int. Workshop on Modeling, Analysis and Simulation of Computer and Telecommunication Systems (MASCOTSx2019;95), pp. 135-141, Durham, NC, USA, 1995.

    Google Scholar 

  25. E. Gelenbe and F. Batty, “Application of the Random Neural Network Model to the Minimum Graph Covering”, Neural Networks: Advances and Applications 2 (E. Gelenbe ed.) North-Holland, 1992.

    Google Scholar 

  26. E. Gelenbe and W. Jin, “Convergence of the numerical iteration for the steadystate distribution of G-networks”, submitted for publication, May 1995.

    Google Scholar 

  27. E. Gelenbe, P. Glynn and K. Sigman, “Queues with Negative Arrivals”, Journal of Applied Probability, 28, pp. 245–250, 1991.

    Article  MathSciNet  MATH  Google Scholar 

  28. E. Gelenbe, A. Stafylopatis and A. Likas, “Associative Memory Operation of the Random Network Model”, Proc. Int. Conf. on Artificial Neural Networks, Amsterdam, North-Holland, 1991.

    Google Scholar 

  29. E. Gelenbe and P. Schassberger, “Stability of Product Form G-Networks”, Probability in Engineering and Informational Sciences, Cambridge University Press, England, 6, pp. 271–276, 1992.

    Google Scholar 

  30. E. Gelenbe, V. Koubi and F. Pekergin, “Dynamical Random Neural Network Approach to the Traveling Salesman Problem”, Proc. Conf. on Systems, Man and Cybernetics, Illinois, USA, 1993.

    Google Scholar 

  31. E. Gelenbe, O.W. Boxma, J.M. Fourneau, P.G. Harrison, M. Hernandez and E. Pitel, “G-networks”, Hot Topics Session, ACM-SIG METRICS/ IFIP WG 7.3 Symposium on System Performance Evaluation, Ottawa, May 1995.

    Google Scholar 

  32. P.G. Harrison and E. Pitel, “Sojourn Times in Single Server Queues with Negative Customers”, Journal of Applied Probability, 30, pp. 943–963, 1993.

    Article  MathSciNet  MATH  Google Scholar 

  33. P.G. Harrison and E. Pitel, “The M/G/l Queue with Negative Customers”, Proceedings of the 4th QMIPS (Queueing Modeling in Parallel Systems) Workshop, London, England, pp. 185-213, Apr. 1994.

    Google Scholar 

  34. P.G. Harrison and E. Pitel, “Response Time Distributions in Tandem G-networks”, to appear in Journal of Applied Probability, Mar. 1995.

    Google Scholar 

  35. W. Henderson, “Queueing networks with negative customers and negative queue lengths”, Journal of Applied Probability, 30, pp. 931–942, 1993.

    Article  MathSciNet  MATH  Google Scholar 

  36. W. Henderson, B.S. Northcote and P.G. Taylor, “Modeling using queueing networks with signals”, ITC 13, 1991.

    Google Scholar 

  37. W. Henderson, B.S. Northcote and P.G. Taylor, “Geometric equilibrium distributions for queues with interactive batch departures”, Annals of Operations Research, 48, pp. 493–511, 1994.

    Article  MathSciNet  MATH  Google Scholar 

  38. W. Henderson, B.S. Northcote and P.G. Taylor, “Networks of customer queues and resource queues”, ITC 14, 1994.

    Google Scholar 

  39. M. Hernández, “Virus Transmission in a Computer Network”, Research Report LAMIFA, Université d’Amiens, France, to appear, 1995.

    Google Scholar 

  40. M. Hernandez and J. Aguilar, “A Simulator for Task Assignment in a Distributed System Subject to Failures”, Proc. of the 4th QMIPS (Queueing Modeling in Parallel Systems) Workshop, London, England, pp. 89-106, Apr. 1994.

    Google Scholar 

  41. M. Hernández and J-M. Fourneau, “Modeling Defective Parts in a Flow System using G-Networks”, Proc. Workshop on Performability Modeling of Computer and Communication Systems, Le Mont St-Michel, France, Jun. 1993.

    Google Scholar 

  42. C. Hubert, “Supervised Learning and Retrieval of Simple Images with the Random Neural Network”, Proc. 7th Int. Symp. on Computer and Information Sciences (ISCIS), Antalya, Turkey, 1992.

    Google Scholar 

  43. D. Merle, D. Potier and M. Véran, “A Tool for Computer Systems Performance Analysis”, Performance of Computer Installations, Ed. Ferrari D., Amsterdam, North-Holland, pp. 195-213, 1978.

    Google Scholar 

  44. M. Mokhtari, “Réseau Neuronal Aléatoire: Applications à l’apprentissage et à la reconnaissance d’images”, PhD Thesis, Univ. Paris V, France, Jan. 1994.

    Google Scholar 

  45. “PAWS: A User Guide”, Information Research Ass., Austin, TX, USA, 1983.

    Google Scholar 

  46. C.D. Pegden, “Introduction to Siman”, Systems Modeling Corp., State College, PA, USA, 1984.

    Google Scholar 

  47. C.H. Sauer and E.A. MacNair, “Simulation of Computer Communication Systems”, Englewood Cliffs, Prentice-Hall, USA, 1983.

    Google Scholar 

  48. M. Véran and D. Potier, “QNAP2: A Portable Environment for Queueing Systems Modeling” Int. Conf. on Modeling Techniques and Tools for Performance Analysis, North-Holland, pp. 25-63, 1984.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 1995 ECSC-EC-EAEC, Brussels-Luxembourg

About this chapter

Cite this chapter

Chabridon, S., Gelenbe, E., Hernández, M., Labed, A. (1995). G-Networks: A Survey of Results, a Solver and an Application. In: Baccelli, F., Jean-Marie, A., Mitrani, I. (eds) Quantitative Methods in Parallel Systems. Esprit Basic Research Series. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-79917-4_7

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-79917-4_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-79919-8

  • Online ISBN: 978-3-642-79917-4

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics