MEAN-VALUE ANALYSIS FOR QUEUING NETWORK MODELS WITH INTERVALS AS INPUT PARAMETERS

Mean value analysis (MVA) is a well-known solution technique for separ able closed queueing networks used in performance modeling of computer and communication systems. In many cases, like for sensitivity analys is or with inaccurate model input parameters, intervals are more appro priate as model inputs than single values. This paper presents a versi on of the MVA algorithm for separable closed queueing networks with on e customer class consisting of load-independent queueing centers as we ll as delay devices, which accepts both single values and intervals as input parameters in an arbitrary combination. Monotonicity of the mod el outputs with respect to all input parameters is proved and these mo notonicity properties are used to construct a low cost interval-versio n of the MVA algorithm providing exact output intervals as results. Th us, dependency problems commonly arising with the interval evaluation of arithmetic expressions are avoided without significant increase in computation costs. Additionally, asymptotic results for the performanc e measure intervals obtained through interval-based analysis and corre sponding bottleneck analysis are presented. (C) 1998 Elsevier Science B.V.