Assessment of QOS indicators of a network with UDP and TCP traffic under a node peak load mode
DOI:
https://doi.org/10.15587/1729-4061.2024.299124Keywords:
Markov model, network traffic, network node, mass service systemAbstract
The object of research is Markov models of network nodes with UDP (User Datagram Protocol) and TCP (Transmission Control Protocol) traffic and their differences.
The task solved is the lack of Markov models of network nodes describing the behavior of TCP traffic from the point of view of packet retransmissions and packet delivery guarantees.
Markov models of network nodes describing traffic behavior with guaranteed packet delivery have been further advanced. Given the comparison of the models, the differences from the classic models serving TCP traffic were shown, for each packet flow, an additional dimensionally was added to the graph of states and transitions, which takes into account the retransmission of a lost packet. The comparison graph shows similar behavior of queue length and packet loss for both types of traffic. But the nature of the curves is different. With TCP traffic, packet loss can exceed 5 percent. In addition, lost packets must be retransmitted, which increases the load on the network node.
More failures and packet queue lengths at a network node during peak load typically occur with TCP traffic compared to UDP traffic. At peak load, the difference in service failures can reach 20–30 percent. The main reason is that TCP uses flow control and rate-limiting mechanisms to avoid network congestion and ensure efficient data transfer between nodes.
The Markov model of TCP traffic requires an additional dimensionally on the graph of states and transitions, which affects the behavior of queues and packet failures.
The investigated problem was solved due to the universality and diversity of the mathematical apparatus of Markov mass service systems.
The results could be used in network modeling software products for building and reengineering the topology of electronic communications networks at enterprises and organizations
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Copyright (c) 2024 Pavlo Pustovoitov, Vitalii Voronets, Oleksandr Voronets, Halyna Sokol, Maksym Okhrymenko
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