Information and telecommunication sciences: international research journal, Vol. 14, N. 2
Постійне посилання зібрання
Переглянути
Перегляд Information and telecommunication sciences: international research journal, Vol. 14, N. 2 за Ключові слова "621.391"
Зараз показуємо 1 - 2 з 2
Результатів на сторінці
Налаштування сортування
Документ Відкритий доступ Adjusting the parameters of machine learning algorithms to improve the speed and accuracy of traffic classification(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2023) Astrakhantsev, Andrii A.; Globa, Larysa S.; Davydiuk, Andrii M.; Sushko, Oleksandra V.Educational and Research Institute of Telecommunication Systems Igor Sikorsky Kyiv Polytechnic Institute, Kyiv, Ukraine Background. Telecommunications developments lead to new mobile network technologies and especially 5G, which has only recently been launched, sixth generation of which is already under active development. The development of new technologies influence on both types of mobile traffic (V2V, IoT) and leads to the significant increase in the volume of existing traffic types. Currently, existing methods of traffic processing are not adapted to such changes, which may lead to a deterioration in the quality of service. Objective. The purpose of the paper is to analyze the effectiveness of machine learning algorithms to solve the task of traffic classification in mobile networks in real time. Methods. The method of solving the problem of increasing the efficiency of information processing is the introduction of new algorithms for traffic classification and prioritization. In this regard, the paper presents the urgent task of analyzing the effectiveness of machine learning algorithms to solve the task of traffic classification in mobile networks in real time. Results. Comparison indicated the best accuracy of the ANN algorithm that was achieved with the number of hidden layers of the network equal to 200. Also, the research results showed that different applications have different recognition accuracy, which does not depend on the total number of packets in the dataset. Conclusions. This proceeding solves the urgent problem of increasing the efficiency of the mobile communication system through the use of machine learning algorithms for traffic classification. In this regard, it can be concluded that the most promising is the application of algorithms based on ANN. In future the aspect of anomaly detection based on traffic classification and traffic pattern preparation should be investigated, as this process allows detecting attacks to network infrastructure and increase mobile network security.Документ Відкритий доступ Optimizing hard qos and security with disjoint path routing(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2023) Lemeshko, Oleksandr V.; Yeremenko, Oleksandra S.; Yevdokymenko, Maryna O.; Sleiman, BatoulThe combination of secure routing and hard QoS is a worthwhile topic that involves designing and implementing network protocols and systems that can provide high performance and robust protection for data flow due to shared goals. Secure QoS routing over disjoint paths is a challenging problem that requires balancing the trade-off between network security and bandwidth guarantees. Objective. This article investigates a mathematical model that can address secure QoS routing by formulating it as an optimization problem with a linear objective function and linear or bilinear constraints. The objective function aims to minimize the paths compromise probability, while the constraints ensure that the total bandwidth of the paths meets the QoS requirements. Methods. We use computer simulation of hard QoS and security with disjoint path routing. Also we use mathematical programming methods in order to describe secure QoS routing. Results. The article presents a numerical study of the model using different scenarios and parameters. The results show that the model can effectively provide secure QoS routing over disjoint paths with a high bandwidth guarantee level and a low compromise probability. The work analyses the sensitivity of the solutions to the QoS requirements and reveals that there is usually some margin in the bandwidth provision. Conclusions. The proposed model is a promising tool for secure QoS routing over disjoint paths in various network environments.