Information and telecommunication sciences
Постійне посилання на фонд
ISSN 2411-2976 (Online), ISSN 2312-4121 (Print)
Періодичність: 2 рази на рік
Рік заснування: 2010
Тематика: теорія телекомунікацій та обробка сигналів; побудова сучасних та перспективних мереж; безпроводові технології та системи; керування в системах та мережах телекомунікацій; моделювання та оптимізація систем і мереж; програмні засоби та інформаційні ресурси телекомунікацій; кабельні та волоконно-оптичні системи; мікрохвильова техніка та терагерцові технології; історія телекомунікацій.
Попередня назва: Telecommunication Sciences (до 2013 року)
Офіційний сайт: https://infotelesc.kpi.ua/
Рік заснування: 2010
Тематика: теорія телекомунікацій та обробка сигналів; побудова сучасних та перспективних мереж; безпроводові технології та системи; керування в системах та мережах телекомунікацій; моделювання та оптимізація систем і мереж; програмні засоби та інформаційні ресурси телекомунікацій; кабельні та волоконно-оптичні системи; мікрохвильова техніка та терагерцові технології; історія телекомунікацій.
Попередня назва: Telecommunication Sciences (до 2013 року)
Офіційний сайт: https://infotelesc.kpi.ua/
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Перегляд Information and telecommunication sciences за Автор "Astrakhantsev, Andrii A."
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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 Analysis of routing protocols characteristics in ad-hoc network(National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2024) Hryschuk, Iryna A.; Astrakhantsev, Andrii A.; Pedan, Stanislav I.; Globa, Larysa S.Background. Wireless ad-hoc networks are becoming increasingly prevalence in remote areas, in extreme environments, even in military operations, and in scenarios where setting up infrastructure networks is not possible. Research of ad-hoc routing protocols problems allows improving the efficiency of their operation in conditions of high variability in packet loss or instability of network operation when the speed of users changes. Objective. The purpose of the paper is analysis of packet loss dependency from a network operation time, study of a user speed influence on a network efficiency, and research of network operation efficiency with different routing protocols. Methods. The method of routing protocols efficiency evaluation is the simulation of their operation in an ad-hoc network on a test data set and research of a network indicators dependency in time under different loads and changing mobility of users. Results. The conducted research demonstrated that user’s mobility at different speeds significantly affects the network operation as a whole. The instability of users' positions leads to a significant increase in route search time and packet transmission time. Among researched GPSR, DSDV, and AODV protocols, the latter proved to be the best because it has the lowest percentage of data loss and the lowest average time of message send and receive operations. Conclusions. The work is dedicated to the actual problem of developing and setting parameters of ad-hoc network. Received research results indicate the need to choose the optimal routing protocol depending on specific application conditions, such as user movement speed and network stability. The proposed solutions can be the first stage of complex processing of packets in the mobile network and justify the choice of AODV protocol as a basis for further improvement.Документ Відкритий доступ Developing a computer vision re-identification system(National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2020) Ostapenko, Maksym S.; Shtogrina, Olena S.; Globa, Larysa S.; Astrakhantsev, Andrii A.; Siemens, EduardДокумент Відкритий доступ Improved cluster management method for industrial “Internet of things” networks(National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2020) Davydiuk, Andriy M.; Astrakhantsev, Andrii A.Документ Відкритий доступ Noise resistance of remote authentication via LTE network(National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2020) Astrakhantsev, Andrii A.; Liashenko, Galyna E.; Shcherbak, Anna O.