APPLICATION OF THE SLIDING WINDOW MECHANISM IN SIMULATION OF COMPUTER NETWORK LOADING PARAMETERS
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Abstract
The subject of the study in the article is the data transfer processes in computer networks from the point of view of the network performance indicators, in particular, overload parameters. The purpose of the work is to create a simulation model of the behavior of a computer network, taking into account the mechanism of the "sliding window" and to demonstrate its work using a test example in combination with the previously proposed algorithms. The following tasks are solved in the article: analysis of the network as a complex multilevel system and isolation of the problems related to the transport layer of the OSI model; consideration of tasks that are solved by the transport layer of the data network; creation of the mechanism of modeling of functions of "sliding window"; demonstration of model work. The following research methods are used: basics of system analysis, models of network functioning, simulation modeling method. The following results were obtained: Based on the results of previous studies, the article proposes a new model of computer network behavior over a period of time. This model is based on the principles of simulation modeling, which became possible because of the certain fractal properties of incoming traffic, that is one of the initial data for the simulation. In the process of development, the seven-level OSI model was taken as the basic network model and its four lower levels were selected. Ensuring reliable information transmission at all protocol levels is based on the mechanisms of acknowledgement and "sliding window". The proposed model can reduce the amount of user data directly for each of the directions in a proportion directly proportional to their utilization of the specified congested channel. It is proposed to use a correction vector for each direction of information transmission in the model. Conclusions: The adequacy of the developed model is confirmed on the basis of practical calculations of the test case. The practical value of this model is the ability to predict bottlenecks when creating a computer network, or vice versa, to point out the redundancy of certain solutions in order to save significant funds in the future for providers and operators of communication services.
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