№1, 2022


Ramiz H. Shikhaliyev

To ensure the efficiency of management, the security of computer networks (CN), as well as to ensure the required level of quality of service for network applications, accurate and up-to-date information on the state of the CN is required. This information can be obtained through continuous active monitoring of the quantitative characteristics of the CN. Thus, active monitoring becomes an important tool for ensuring the efficiency of management and security of the CN. However, continuous active monitoring, especially of large networks, can lead to congestion of network channels, which can reduce the effectiveness of monitoring the CN. Consequently, with active monitoring of the CN, it is necessary to manage the use of resources (channel and computational) of the network and reduce the load on the network. To solve this problem, this paper proposes a method for intelligent planning of monitoring of the CN. Using machine learning algorithms, can be analyzed the state and performance of the CN and acquire knowledge that can be used to determine the most appropriate rules for monitoring the CN. Thus, it is necessary to find such monitoring rules that will ensure the effectiveness of monitoring the CN. The proposed method can reduce the impact of monitoring on network performance, and on the operation of network applications (pp.38-42).

Keywords: computer networks, network monitoring, intelligent scheduling of monitoring, machine learning
DOI : 10.25045/jpit.v13.i1.05

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