Towards a Performance Modelling Environment: News on Hit

  • H. Beilner
  • J. Mäter
  • N. Weißenberg


HIT is a comprehensive software tool supporting the model-based evaluation of computing system performance. HIT models exhibit a highly structured view of the systems to be assessed, based on (vertical) functional hierarchies and (horizontal) modularization as employed in modern software engineering and hardware architecture approaches. Analysis of HIT models is provided by analytic-algebraical, analytic-numerical, exact and approximate techniques and by discrete-event simulation. Both model description and model analysis utilize the model structure for convenient problem specification and efficient evaluation, respectively. Particular emphasis is placed on decomposition and aggregation options and on a mixed (heterogeneous) use of different analysis techniques. Great care is also employed with respect to tool handling aspects. This paper describes recent extensions of the HIT modelling environment and illustrates it by way of an extended office model example.


Component Type Load Pattern Total Model Type Office Queueing Network 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. Baskett, F., Chandy, K. M., Muntz, R. R. and Palacious, F. G., 1975, Open, Closed and Mixed Networks of Queues with Different Classes of Customers, JACM, vol. 22, no. 2Google Scholar
  2. Beilner, H., 1981, “Algorithms for Evaluating Separable, Mixed, State-Independent Queueing Networks or Improving (Slightly) on Mean Value Analysis”, Forschungsbericht Fachbereich Informatik Universität Dortmund, Nr. 124Google Scholar
  3. Beilner, H., ed., 1985, “Messung, Modellierung und Bewertung von Rechensystemen”, Informatik-Fachberichte, vol. 110, SpringerGoogle Scholar
  4. Beilner, H. and Mäter, J., 1985, COPE: Past, Presence and Future, in: Potier (1985)Google Scholar
  5. Beilner, H. and Noack, F., “DOQ3: Yet another algorithm for Mixed Separable Networks”, in preparationGoogle Scholar
  6. Beilner, H. and Scholten, H., 1985, Strukturierte Modellbeschreibung und strukturierte Modellanalyse: Konzepte des Modellierungswerkzeuges HIT, in: Beilner (1985)Google Scholar
  7. Beilner, H. and Stewing, F. J., 1987, Concepts and Techniques of the Performance Modelling Tool, HIT, in: “Discrete Event Simulation and Operation Research”, Adelsberger, H. H. and Broeckx, F., ed’s., Simulation CouncilsGoogle Scholar
  8. Chandy, K. M., Herzog, U. and Woo, L., 1975, Parametric Analysis of Queueing Networks, IBM Journal Res. Dev., vol. 19, no. 1Google Scholar
  9. Chandy, K. M. and Neuse, D., 1982, Linearizer: A Heuristic Algorithm for Queueing Network Models of Computing Systems, CACM. vol. 25, no. 2Google Scholar
  10. Eager, D. L. and Sevcik, K. C., 1986, Bound Hierarchies for Multiple Class Queueing Networks, JACM. vol. 33, no. 1Google Scholar
  11. Fishman, G. S., 1978, “Principles of Discrete Event Simulation”, John Wiley & SonGoogle Scholar
  12. Hong, J. P. and Kim, G., 1983, Class Dependent Queueing Disciplines with Product Form Solutions, in: “Performance ‘83”, Agrawala, A. K., Tripathi and S. K., ed’s., North HollandGoogle Scholar
  13. Jobmann, M. R., 1985, Modellbildung und-analyse von Rechensystemen mit Hilfe des Programmsystems MAOS, in: Beilner (1985)Google Scholar
  14. Litzba, D., 1985, “Auswertung von Simulationsdaten mittels autoregressiver Modelle”, Forschungsbericht Fachbereich Informatik Universität Dortmund, Nr. 203Google Scholar
  15. Müller, B., 1982, Decomposition Methods in the Construction and Numerical Solution of Queuing Network Models, in: “Performance ‘81”, F. J. Kylstra, ed., Amsterdam, North HollandGoogle Scholar
  16. Müller, B., 1985, NUMAS: A Tool for the Numerical Modelling of Computer Systems, in: Potier (1985)Google Scholar
  17. Müller-Clostermann, B., 1988, “HIT — An Introduction”, Projektbericht, Informatik IV, Universität DortmundGoogle Scholar
  18. Müller-Clostermann, B. and Rosentreter, G., 1987, Synchronized Queueing Networks, Concepts, Examples and Evaluation Techniques, in: Herzog, U. and Paterok M., ed’s., “Informatik Fachberichte”, vol.154, SpringerGoogle Scholar
  19. Müller, B. and Weißenberg, N., 1986, Using SIMULA 67 for the Implementation of a Hierarchical Tool for Modelling and Performance Evaluation of Computing Systems, in: “Proc. 14th SIMULA Users’Conference”, StockholmGoogle Scholar
  20. Potier, D., ed., 1985, “Modelling Techniques and Tools for Performance Analysis”, North HollandGoogle Scholar
  21. Reiser, M., 1979, Mean Value Analysis of Queueing Networks — A New Look at an Old Problem, in: “Performance of ComputerSystems”, Arató, M., Butrimenko, A., Gelenbe, E., ed’s, North HollandGoogle Scholar
  22. Sauer, C. H. and MacNair, E. A., 1985, The Evolution of the Research Queueing Package, in: Potier (1985)Google Scholar
  23. Stewart, W. J., 1978, A comparison of numerical techniques in Markov modelling, CACM, vol.21, no. 2Google Scholar
  24. Veran, M. and Potier, D., 1985, QNAP2: A Portable Environment for Queueing Systems Models, in: Potier (1985)Google Scholar
  25. Wolf, H., 1986, Outil de Modélisation et d’Evaluation HIT, Journées d’Etudes Modélisation et Evaluation de Systèmes Informatique, Sophia AntipolisGoogle Scholar

Copyright information

© Plenum Press, New York 1989

Authors and Affiliations

  • H. Beilner
    • 1
  • J. Mäter
    • 1
  • N. Weißenberg
    • 1
  1. 1.Informatik IVUniversität DortmundGermany

Personalised recommendations