On the Kendall's classification

The features of the existing classification of queuing systems are considered, its disadvantages are shown. Only the laws of time intervals distribution between neighboring requests and time intervals for processing requests are used as the main flows characteristics. The main disadvantage is the lack of information about the correlation and cross-correlation flows properties. It is shown that flows that have the same distribution laws but different correlation properties can form queues where values differ by several orders of magnitude. Flows controlled by the Markov chain and, in particular, examples of hyperexponential flows classification are considered. It is shown that this kind of flows can have the same probability distribution laws for time intervals between neighboring requests, but significantly different queue sizes caused by the difference in the flows correlation properties. Another disadvantage of the Kendall’s classification is inability to classify systems by the nature of changes in the input load.