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Mean Value Analysis Approximation



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77 Mean Value Analysis Approximation for Multiple Server Queueing Networks Ian F Akyildiz School of lnformation and Computer Science Georgia Institute of Technology Atlanta Georgia 30332 0280 U S A Gunter Bolch IMMDIV Universitiit Erlangen Niirnberg Martensstrasse 1 8520 Erlangen Fed Rep Germany Received May 1986 Revised 3 June 1987 An approximation of mean value analysis is presented for queueing networks containing multiple server stations The approximation is based on the estimation of the conditional marginal probabilities used by the mean residence time formula in mean value analysis A comparison against classical mean value analysis allows us to determine the accuracy of our algorithm In all investigated network models the approximate results vary from the exact results by less than four percent on the average This approximation method has all the advantages of classical mean value analysis specifically it is easy to implement and has a very short run time Keywords Queueing Network Analytical Method Mean Value Analysis Conditional Marginal Probability 1 Introduction Mean value analysis has enjoyed widespread popularity during recent years as an exact technique for providing solutions to product form queueing networks The basic concept of mean value analysis is the application of an iterative procedure to calculate mean residence time system throughput and the mean number of jobs A number of studies about mean value analysis has been published in the last few years I F Akyildiz was born in 1954 in Istanbul Turkey He received his B S 1978 M S 1981 and Ph D 1984 degrees in Computer Science from the University of Edangen Niirnberg Fed Rep Germany From 1981 through 1985 he served as a Scientific Employee in the Informatik IV Operating Systems chair of Prof F Hoffman Department at the University of Erlangen Niirnberg During that time he coauthored a text book titled Analysis of Computer Systems in German published by Teubner Verlag in 1982 In January of 1985 he



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