The paper presents a system of models of queuing networks, which are divided into three groups: static models, dynamic flow models, and residence time probability density evolution models.
The proposed system of models depicts the key features of information transfer:
the structure of the queuing network, the network algorithms (routing and flow control), queue processing rules in the network nodes, reservation rules elements of the network, network parameters, input flow parameters. Next, the models allow to estimate the following information route parameters: information delivery time, connection time, etc. Also the models allow to estimate the probabilistic features of a queuing network such as reliability of message delivery, connection probability, etc. Additionally, the models can compute input stream intensity change, features of transient processes in non-stationary nets.
Finally, the models describe data transfer in networks of different topology, different routing and flow control procedures, general features of the networks.