INTEGRAL METHODS FOR EVALUATING THE PERFORMANCE OF PACKETSWITCHED NETWORKS: ANALYSIS AND FORMULATION

DOI: 10.31673/2786-8362.2024.025073

Abstract

The article discusses integral methods for evaluating the
performance of packet-switched networks, which ensure stability and service efficiency under multi-service
traffic conditions. In modern telecommunications networks, ensuring Quality of Service (QoS) and Quality
of Experience (QoE) is critically important as they help achieve high user satisfaction and ensure reliable
communication. Standard approaches for assessing network performance typically rely on individual
metrics, such as latency, packet loss, and jitter, but they do not always provide a comprehensive
understanding of the network's overall state. The integral quality metrics proposed in the study allow the
combination of different parameters to produce a generalized performance assessment that accounts for
short-term fluctuations under high loads and changing traffic.
The goal of the study is to develop integral metrics that enable network operators to improve
performance monitoring and service quality in multi-service networks. The calculation of the integral
connection quality metric is described, based on comparing the area where the parameter exceeds a
threshold value with the maximum possible area. The formulas for the integral metric and its applications
in comparing different communication channels are presented. The impact of nonlinear effects in packet
traffic transmission, particularly the exponential growth of indicator values with performance degradation,
is considered. A formula for the integral metric is proposed, which incorporates an exponential evaluation
function for a more accurate performance assessment. Using this approach, the developed method allows
for comparative analysis of network connection performance based on generalized quality metrics that
reflect network behavior under mixed traffic conditions.
The developed methods and metrics can form the basis for improving network management systems
in dynamic load conditions and heterogeneous user requirements. This not only ensures high service quality
but also increases user satisfaction under various network operating conditions.

Keywords: network performance, Quality of Service (QoS), Quality of Experience (QoE), bandwidth,
integral assessment, single-threshold assessment, multi-threshold assessment, integral quality metric

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