Piskovsky V.O.

5G NR communication systems use antenna arrays for directional transmission and reception, which in turn contributes to increased communication performance and efficiency. For duplex systems with frequency division of channels, feedback about the channel status is important. The code page for the configuration of the base station’s antenna array and the antenna ports of the client device is selected through the exchange of reports. The essence of the work is to optimize the exchange procedure, apply and study data compression methods.

The efficiency of network services depends on how applications are distributed in the network. At the same time, these services are to be provided with a certain quality of services and experience for users, i.e.:

1) access to information “at any time anywhere”;

2) seemless integration of informational systems;

3) timely monitoring and analysis of different data sources;

4) migration from a centralized scheme “data download with cleaning followed by analysis and distribution” to the scheme “distributed placement and preprocessing of data and, if necessary, subsequent loading, analysis and distribution”.

One of the key preconditions to provide an acceptable level of services is forecasting the execution time of network services on a variety of virtualization platforms and physical equipment.

The work analyzes approaches to predicting temporal characteristics of network services. The methods are based on operational log data of services and physical equipment, take into account the current and predictable state of hardware and software resources. Among the solutions considered are machine learning models, including a random forest, multilayer perceptrons, and convolutional neural networks.