Abstract
A method is described for finding analytically the normalizing constants (and hence also other performance characteristics) of stochastic networks with different classes of messages.
Similar content being viewed by others
Literature Cited
A. I. Gerasimov, “Analysis of distributed real-time computing systems,” Izv. Vyssh. Uchebn. Zaved. Priborostr.,22, No. 12, 29–34 (1989).
A. I. Gerasimov, “Computing the throughput of the Sirena MIS,” Prib. Sist. Uprav., No. 6, 2–4 (1982).
J. P. Buzen, “Computational algorithms for closed queueuing networks with exponential servers,” Comm. ACM,16, No. 9, 527–531 (1973).
S. C. Bruell and G. Balbo, “Computational algorithms for closed queueing networks,” Oper. Program. Syst., No. 7, 190–197 (1982).
A. I. Gerasimov, “Analysis of queueing networks by polynomial approximation,” Probl. Contr. Inform. Theory,12, No. 3, 219–228 (1983).
A. I. Gerasimov, “The POLAP package for computation of stochastic networks by polynomial approximation,” Algoritmy Programmy, Moscow, No. 4(55), 33 (1983) (Inform. Byull. Gos. Fonda Algoritmov i Programm SSSR, VNTITsentr No. POO6246).
A. I. Gerasimov, “Approximate method of analysis of closed, open, and mixed stochastic systems,” in: Deterministic and Stochastic Control Systems [in Russian], Nauka, Moscow (1984), pp. 6–18.
F. R. Moore, “Computational model of a closed queueing network with exponential servers,” IBM J. Res. Develop.,16, 567–572 (1972).
P. G. Harrison, “A note on cycle times in tree-like queueing networks,” Adv. Appl. Probab.,16, No. 1, 216–219 (1984).
P. G. Harrison, “On normalizing constants in queueing networks” Oper. Res.,33, No. 2, 464–468 (1985).
J. A. Aseltine, Transform Methods in Linear System Analysis, McGraw-Hill, New York (1958).
H. A. Helm, “The z-transformation,” Bell Syst. Techn. J.,38, No. 1, 178–196 (1959).
Additional information
Translated from Kibernetika, No. 3, pp. 98–102, May–June, 1991.
Rights and permissions
About this article
Cite this article
Gerasimov, A.I. Analytical method for determining the characteristics of stochastic networks with different classes of messages. Cybern Syst Anal 27, 442–449 (1991). https://doi.org/10.1007/BF01068325
Received:
Issue Date:
DOI: https://doi.org/10.1007/BF01068325