Oleksandr Lavrut

Work place: Tactics Department, Hetman Petro Sahaidachnyi National Army Academy, Lviv, 79012, Ukraine

E-mail: alexandrlavrut@gmail.com

Website: https://orcid.org/0000-0002-4909-6723

Research Interests:

Biography

Oleksandr Lavrut is a Professor in the Department of Tactics at Hetman Petro Sahaidachnyi National Army Academy. In 2020, he received his Doctor of Engineering Sciences degree in Information Systems and Technologies. He defended his dissertation for the degree of Candidate of Technical Sciences in 2003 in the field of "Cybernetics, Control Systems and Communications". He also holds the academic title of Professor, which he received in 2021. Oleksandr has authored over 250 publications, and his primary research interests focus on the theoretical aspects of construction telecommunications networks, as well as on the creation and operation of control and communication systems for various purposes. His work also covers machine learning and cybersecurity.

Author Articles
Application of Tensor Networks Analysis to Optimize Traffic Management in a Critical Information and Telecommunications Network

By Oleksandr Lavrut Tetiana Lavrut Victoria Vysotska Zhengbing Hu Yuriy Ushenko Dmytro Uhryn

DOI: https://doi.org/10.5815/ijigsp.2025.04.08, Pub. Date: 8 Aug. 2025

The article investigates the task of optimising traffic management in critical information and telecommunication networks in order to ensure a guaranteed quality of user service, particularly in emergencies. A method of tensor analysis of networks is proposed, using a formalised description of the system in the form of tensors of message lengths, delays and bandwidth of channels. The network is modelled as a simplified complex, and routing is implemented through a tensor equation of connection between network parameters in different coordinate systems. Experimental calculations using examples with dynamically variable topology have shown:

•Reduction of average multipath message delivery latency by 9–40% depending on traffic intensity,
•Probability of packet delivery at or above 0.999 under high loads (200-300 messages/s),
•Zero jitter due to the even distribution of delays between paths,
•The ability to adaptively fragment messages in nodes to reduce latency,
•Increasing the efficiency of resource use compared to single-track models.
 
The use of a tensor apparatus provides stable and scalable routing in an unstable network topology. The method allows you to take into account the heterogeneity of traffic, adapt to the loss of nodes or channels, and maintain guarantees of quality of service in real time. The proposed approach is of practical importance for information and telecommunication systems used in emergencies, in particular for coordinating the actions of emergency rescue services, emergency medicine, civil protection, military units, control of drones and robotic means in the face of infrastructure loss. Potential stakeholders include state and municipal security services, operators of critical networks (energy, transport, healthcare), developers of automated control systems, and manufacturers of secure communication equipment. The proposed method can be integrated into decentralised networks with limited resources and variable topology, where traditional routing approaches do not guarantee sufficient quality of service.

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