Перегляд за Автор "Globa, Larysa S."

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    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.
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    Advanced approach to Web Service Discovery and Selection
    (National Technical University of Ukraine “Kyiv Polytechnic Institute”, 2014) Pukhkaiev, Dmytro S.; Oleksenko, Oleksii O.; Kot, Tetiana M.; Globa, Larysa S.; Schill, Alexander
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    An Approach for Virtualized Network Slices Planning in Multiservice Communication Environment
    (National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2019) Globa, Larysa S.; Sulima, Svitlana V.; Skulysh, Mariia A.; Zhuravel, Anastasiia S.
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    An approach to dynamic web service composition
    (National Technical University of Ukraine “Kyiv Polytechnic Institute”, 2013) Pukhkaiev, Dmytro S.; Kot, Tetiana M.; Globa, Larysa S.
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    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.
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    An approach to the Internet of Things system with nomadic units developing
    (IEEE, 2016) Globa, Larysa S.; Ishchenko, Ivan; Gvozdetska, Nataliia; Zakharchuk, Andrii; Zvonarov, Oleh
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    Comparison of optimization strategies and estimation techniques for radio network planning and optimization problems
    (National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", 2023) Prokopets, Volodymyr A.; Globa, Larysa S.
    Background. Radio network planning is one of the main phases of the cellular network lifecycle, as it determines capital and operating costs and allows system performance evaluation at any given time. An accurate and comprehensive analysis of existing network statistics is necessary for proper cell planning during network expansion. These statistics are collected throughout the life cycle of the cellular network and usually have certain imperfections (heterogeneity of statistics, which have different densities in different parts of the search space, up to the presence of significant voids, etc.) The system describing the functioning of the radio network can be represented as a black box because its internal processes are too complex to be defined by mathematical functions. This determines the need to use appropriate tools. Objective. The purpose of the paper is to create a toolkit that allows finding the proper relationships between network parameters to define target values that will help to build an effective network plan in terms of performance and costs for its creation and operation. The tools should be able to work efficiently using the minimum set of available statistical data, as well as taking into account their imperfections. Methods. Mathematical estimation and optimization methods are used, namely Ordinary Least Squares, Ridge Regression, Lasso, Elastic-net, LARS lasso, Bayesian Ridge Regression, Automatic Relevance Determination, Stochastic gradient descent, Theil-Sen estimator, Huber Regression, Quantile regression, Polynomial regression. We consider 12 estimation methods in combination with two optimization strategies. Additionally, the method of partial analysis of the search space with different number of configurations is considered. Results. A software package using the Python programming language has been created, which contains a practical implementation of all the considered estimation and optimization methods, as well as tools for evaluating arbitrary configurations of the software package (benchmark) and visualizing the results. The best estimation method is Ordinary Least Squares for finding the optimal configuration of the statistical parameters of the 4G radio network to maximize the download speed. To obtain satisfactory results, it is enough to consider 25 initial and 250 estimated points - a larger number of points will not significantly increase prediction accuracy. Conclusions. The results indicate the possibility of using the created software package for radio network planning tasks. Further research is aimed at expanding the created software package's functionality and considering additional estimation methods and optimization strategies.
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    Complex approach to service development
    (National Technical University of Ukraine “Kyiv Polytechnic Institute”, 2012) Kot, Tetiana M.; Reverchuk, Andrey V.; Globa, Larysa S.; Schill, Alexander
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    Computation of providing services integral quality index
    (National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2018) Globa, Larysa S.; Svetsynska, Ievgeniia S.; Volvach, Ievgen A.
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    Computer-aided workflow designing for QOS control based on ontology
    (National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2020) Globa, Larysa S.; Popova, Maryna A.; Yushko, Nataliia A.; Mirtskhulava, Lela
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    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, Eduard
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    Estimation scheme for improvement of weighted round robin algorithm for requests service in the queues
    (IEEE, 2012) Globa, Larysa S.; Skulysh, Mariia A.
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    Industry 4.0 and modern approaches for big data analytics
    (National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”e”, 2019) Luntovskyy, Andriy O.; Globa, Larysa S.
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    Methodology for knowledge portals development: background, foundations, experience of application, problems and prospects
    (2012) Borovikova, O. I.; Globa, Larysa S.; Novogrudska, Rina L.; Ternovoy, M. Yu.; Zagorulko, G. B; Zagorulko, Yu. A.
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    Model for efficient allocation of network functions in hybrid environment
    (National Technical University of Ukraine “Kyiv Polytechnic Institute”, 2016) Skulysh, Mariia A.; Globa, Larysa S.; Sulima, Svitlana V.
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    Ontology of scientific and educational institutions information
    (National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2020) Globa, Larysa S.; Novogrudska, Rina L.; Zadoienko, Bohdan O.; Yu Junfeng
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    Securing internet of things data
    (National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2019) Globa, Larysa S.; Yamnenko, Julia S.; Kurdecha, Vasyl V.; Trokhymenko, Danylo V.
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    Three-tier architecture for Internet of Things networks
    (National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute”, 2018) Globa, Larysa S.; Kurdecha, Vasyl V.; Shoferivskyi, Andrii S.
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    Tree structure data change detection method
    (National Technical University of Ukraine “Kyiv Polytechnic Institute”, 2014) Molchanov, Yuriy M.; Globa, Larysa S.; Alexeyev, Nikolay O.
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    Модель представления знаний на специализированном интернет-портале в области сопротивления материалов
    (Політехніка, 2012) Глоба, Лариса Сергеевна; Новогрудская, Рина Леонидовна; Globa, Larysa S.; Novogrudsca, Rina L.